#and still training new speech to text software at the same time

[dramamelon]

Working on Cyclonus Week. I'm in the second half of the prompts, finally. To make it really fun, it's developed the plot well beyond the length it's going to be. This happens a lot with event weeks, I've noticed.

That aside, I need to get it finished so I can get well ahead with DriftRod Week. Time just does not slow down to let a person get shit done in a reasonable manner.

[welcome-to-green-hills]

Ok, let me forget about Sonic for one sec. I really like you, Mystery, and I hope you're doing good! I don't know exactly what's happening in Florida that's upsetting you so much, but I still want you to know that I care about you, ok? Your blog makes me really happy! And I really want you to be happy as well ❤

It’s okay, I can explain.

In the United States of America, our coronavirus numbers are up. We are around 4,450,000 people infected and about 152,000 deaths. Not everyone here is able to get a COVID19 test. You can in my town, but you have to make an appointment... that’s about a week or so of waiting. Results of your test won’t come back until 6-8 days later. That data would not be accurate anymore.

Dr. Anthony Fauci, the USA’s leading doctor on the whole pandemic here, says that for each state you should go back on immediate lockdown if you’re state has a 5% risk of getting infected. The state of Florida is 16% positive. We need to be on a lockdown. My state governor said that we shouldn’t be on lockdown, that would upset Trump.

I could care less what that incompetent fool thinks. State governor and Trump.

In the USA, each citizen is entitled to a form of public education. Trump, not the smartest little boy in the whole world, claims that he can cut funding from public schools and send the funding to private schools if we do not force public schools teachers to go back to a brick and mortar school. Legally, he cannot stop funding. That’s been proven. Public education has been defunded—do not dare challenge me that it’s the same as defunding police—before in the past, but to completely stop funding public schools cannot be done. Legally, it would be almost impossible.

My state governor, Ron DeSantis, claimed that he’ll stop funding funding schools in the state of Florida. I’ve done my research, this is what an anthropologist does, and I found that with Florida’s governor and the USA government funding Florida’s schools is not even near 32%. We get all of our school funding from the working people of the town. That’s why when you go to a public school it looks nice.

The plan that I proposed was simple:

Give The state capital the middle finger and say that we’ll lose the 30% for the one year.

Last year Florida’s education was rewarded a surplus of money for the improvement of test scores in students and with what the school did in performance academic wise. We could use a great chunk of that to keep the paychecks flowing to teachers.

Schools earn money for each kid present on campus. This helps factor in school supplies, such as text books and class materials. Have each kid stay enrolled in a public school and collect that check to invest in online software. We can create Blackboard, Google Classrooms, and Canvas rooms for the new year to interact with each kid to help them through the new year.

It’s a state requirement here that kids in public school need to take an online class. If you have all the kids do this now, then you DONT need to worry of a child will graduate will all Florida credits.

We, my town, partnered with the university that I attend. We could work together and create “Hot Spots.” It would be a designated school bus parked in one part of neighborhoods for low-income students, and provide iPads for students to do their work on. The university agreed to help in a townhall meeting.

I also proposed a math problem to school board members:The average substitute teacher makes $75.00-$100.00 dollars around the week that they substitute. Let’s say that for our seven hour school day, we take six class periods. If they’d have to call upon a sub for each teacher that ONE sick kid interacts with, they school would have to pay for a substitute. But think of this also: kids interact with other teachers, teachers aids, and if they come across some in hallways, then they’d need a sub as well. We’re looking at ten subs for just six teachers, as well as those that need to do lunch duty and dismiss kids from school. You’d need six separate subs for each class... and then think about the other teachers that come to interact with one another. We might need more than ten a day. We could need at least 12 or 14 or more. Each student also interacts with that one kid and transitions to another class... think about THAT. It would be cheaper to use the reward money from last year to invest in hotspots and iPads for each student.

You have to pay for a COVID19 test here. It’s supposed to be free, but some people are reporting that they are paying either $23.00 to $2,300 for each test due to the insurance companies’ fee. Not every test goes to a specific place in back, this means that it’s shipped to whatever lab is willing to take it and test the results given to see if you’re infected or not. The school would have to pay for that.

Again, it would be cheaper to have kids stay home rather than have them go to school each day.

DeSantis stopped testing sites in some parts of the state due to Hurricane Isaias. Why is it that testing sites are closed, but not schools? They could move testing sites somewhere else.

There were lots of things that the school board said that educators should do for their students, but somethings that they’ve said, such as opening windows and taking students outside, violates fire safety hazards and an American Teacher’s ALICE training. (ALICE prevents school violence. I’ve been to a couple of schools where there was really bad school violence). This was detailed in my essay.

DeSantis claimed that teachers can take a sabbatical—that means that they have a job, but they won’t be paid for a whole year—if they’re at-risk. My mom is asthmatic. She can’t afford to take a sabbatical. This was what was written in Florida’s opening process plan for the state’s schools.

DeSantis also states that it’s options for masks in schools for kids. Here’s the thing with that. Children are asymptomatic. They carry the virus and spread it. They can get sick, yes, they have different symptoms than we do. Teachers would have to wear the mask. This already endangers younger kids in elementary school, specifically kids between 4-12. When a teacher speaks, kids will need to study the teacher’s mouth on how words and sentences are pronounced. Their face is already covered. In ONE year, that specific age group could have a development issue on how they speak because they are not seeing how certain words are pronounced. You’ll debate that, “oh, they’ll learn this from parents,” but that’s part of the argument. Developing minds need this access all the time. You could have a generation that would require speech therapy. I’ve been in speech therapy due to hearing problems as a child. That’s not fun. The online screen time where the teacher can call via video chat would be much more efficient.

So, yes. There’s a lot on my mind. I’ve given a chunk of what I’ve explained to many school board members AND to DeSantis himself. This is crucial. This is a matter of saving many lives or endangering lives due to COVID19. The answers were there. Now something else is happening because they’re afraid of losing something that’s not even possible in our USA government. I even used lots of citations in the essay that I’ve shared supporting my arguments.

I encourage you all to use your voice. This is what I proposed.

[speech-to-text]

Speech to Text: Use Dictation Software To Write Fast

Are you looking for dictation software? Or do you want a way to transcribe speech notes into text in real-time?

Text software speech will enable anyone to transcribe and write text rather than typing. There are 10 Best Pieces of Text to Speech Software select the most suitable here.

Over the years it has become more affordable and accessible. Transcription services are another popular choice.

When I was working as a journalist, I spent a lot of time interviewing people. One of the most painful things I have to do is transcribe long interviews using the keyboard.

My fingers hurt after spending an hour pressing play and pause and play and pause and typing what the interviewees saying. I also felt pain in the playback speed. Nowadays, I use dictation software like text to speech and transcription software.

Converts previous speeches into text and transcribe first drafts of articles, blog posts, book chapters, and more. The latter is ideal for getting a copy of my work from a typist.

The use of both types of software is useful to avoid the physical pain of typing. and also it is a fast way to create documents, memos, emails, and speeches.

What is Speech to Text Software?

Speech to text or voice dictation software represents spoken transcription technology that converts spoken word into text. This will allow you to write articles, speeches, books, memos, emails, and more with your voice.

Virtual assistant apps respond to voice commands and complete predefined tasks, but speech-to-text technology is for writing spoken words or phrases.

Also known as dictation software, it can include assistive technology features to control your computer/system. It is sometimes available on a mobile app or desktop app and is compatible with various devices.

Why Use Speech to Text Software

Dictation or speech-to-text transcription is much faster than typing.

If I knew what I was writing I could type about five hundred to one thousand words in 30 minutes. On the other hand, I can write up to three or four thousand words in 30 minutes.

Talking about workflow management and turnaround time!

With technology, you don't have to invest in expensive screen reader software or pay exorbitant fees for English transcription. Artificial knowledge has allowed new dictation solutions.

With features like mobile dictation and advanced speech recognition software, spending your days typing your keyboard in Microsoft Word may end.

Digital dictation software is not only a real-time-saver, but it gives you the freedom not to rely on a keyboard to put words on paper.

Digital dictation with the help of artificial intelligence and cheap dictation tools is the future of many writers.

Dictation is ideal if you suffer from RSI or if your finger hurts from typing. You can also order to stand up while walking around the room or without using your hands.

Dictation is also ideal for writing first drafts, but if you are not ready for premium speech-to-text software, let me explain what you can use instead.

The work of any first draft only exists. You should not stop editing yourself when you are writing your first draft.

With dictation, it's hard to edit and write at the same time, which means you'll probably override your daily target word count and get that messy first draft out of your head and into a blank page.

You can not stop dictating, checking your email, browsing Facebook, or doing anything that has nothing to do with writing.

You can use your computer's inbuilt dictation system or other speech recognition programs to start speech-to-text. You can also use Android and iOS - mobile apps - to dictate on the go.

Remember to improve the voice of your dictator to make better use of dictation tools.

Writing a Book By Dictation

Writing a book according to dictation is different from typing a draft or relying on pen and paper.

For example, I wrote the last few books of my Art of Writing non-fiction book. To make this work, I had to outline most of the chapters before handling the index cards first.

Then, I had to train myself to write the whole chapter without editing the typo or solving the problems. Actually, I drafted first and then typed and then edited and rewrote the drafts.

As explained earlier, your voice typing is best for getting your first draft on paper. You still need to edit and format your book, which voice-to-text software cannot achieve.

Dictating your first book:

Keep the background noise to a minimum.

If you use a mobile device or smartphone, use a headset with a microphone.

Make sure you have a fast internet connection, especially if you're using Google Docs on a Chrome browser.

For the end leave the editing and formatting, and do it manually.

Web apps

Speech notes are free browser-based dictation software that allows you to convert your speech into text in your Chrome browser.

It's very easy to set up and once you allow your mic to be used you just have to click on the microphone icon and you're good to go.

Even if you upgrade to its premium version, speech knots are more effective than using transcription services.

You can export your files to .doc or .txt or upload them to Google Drive. It was also available on a mobile app.

Pros and Cons of Dictation Software

Dictation software - game-changer for writers. In various ways, it will improve your writing process and make your life easier.

Pros

Speeding up the writing process

Good in writing in a more conversational style

Dictate as you cook, clean, or exercise

Record notes and ideas regardless of what you are doing

Ideal for people with disabilities

Cons

Take time to customize

Finding and reading foreign names and words can be difficult

It Will did not work properly with large background noise

Editing is more time consuming

Speech to Text Software: The Final Word

Speech-to-text software is usually supported by machine learning and is automated.

A popular but more expensive option is to record an audio file and send it to a human or AI-supported transcription service.

Voice-to-text software exists for authors, such as those mentioned above, as well as Deskshare’s Dictation Pro and Philips SpeechExec Pro.I have used some but not all of them.

Try a free version to find out if dictation software is right for you and see how it fits your style. Once you have the confidence, invest and take your writing career to new heights.

 career to new heights.

[adhdstudybitch]

Practical Tips for ADHD College Students

I know a few posts like this already exist, but I wanted to add my own experiences to the mix in case it would be helpful to someone else. Some of these will look familiar, some not so much.

Disclaimers: 1) What works for me may not work for you, take everything with a grain of salt and experiment, 2) These are what I’m using for a 4-year school but I imagine it would be applicable for any college? I wish I’d known to do some of these things when I was at CC, 3) I won’t pretend that I am an ADHD success story, not yet. I’m still finding my way, learning to cope, learning to thrive. It’s a process.

NOTE: This post is kinda long; if it’s too long I recommend just reading the bolded/italicized headings and only reading the ones that pique your interest :)

Sensory Issues:

Wear comfortable clothing: Screw the mentality that you always have to look your best in college. At the end of the day, feeling hot but ridiculously uncomfortable will trigger sensory issues (especially if you’re someone who is sensitive to certain materials/styles of clothing) and it will impact concentration and can cause a lot of distress. Are you comfortable in those sweatpants, pajama bottoms, baggy shirts? Cool, wear them. 

Stim toys: Love yourself, buy (or make!) stim toys and bring them to school. Can’t speak for CC because I didn’t use stim toys when I went, but at my 4-year school everyone is too busy drowning in deadlines to notice you squishing thinking putty or using a fidget cube under the table. 

Try different stim toys: I used to get caught up on trying to make the more popular stim toys work for me when they didn’t, so I had to experiment a bit to see what worked. It’s not always as simple as cubes, spinners, squishy toys, etc. If you have issues with texture you’ll want to really experiment, especially with things like putty, squishibles, etc. to see what is comfortable and what isn’t. But there’s a big ol’ market out there!

Headphones/Earplugs: The single most helpful sensory detail for me was always bringing my headphones to campus. I get easily overstimulated in uncontrolled situations with lots of different sounds. I make sure my volume is enough to block the noise out, but the songs I choose in these instances are usually familiar, so they don’t provide too much new stimulation when I can’t handle it. I also keep earplugs in my backpack for exams.

Studying/School Related:

If possible, leave your house: This has been one of the hardest changes I’ve had to make because I’m an introvert and genuinely prefer being home. But I’m starting to learn that my ass will not do work 9/10 times when I’m home. Too much to do, too many other things to get done, lots of fun distractions, and cats! So many cats! Unfortunately cats won’t take my exams. I’ve found that the library is okay, but for me small cafes worked much better. Armed with my headphones, some coffee, and an atmosphere that caters to silently getting work done, I’m able to focus longer, and to focus on what I really need to.

Note-taker: Admittedly I’m talking out of my ass on this one, because I haven’t yet done this. But that’s exactly why I want to stress getting a note-taker. My college life would be infinitely better if I’d done this when the semester started; instead, my notes have gaps where I couldn’t concentrate, or couldn’t process what was being discussed, etc. 

Other accommodations: Accommodations for ADHD differ depending on the college, but some of the common ones are: note-takers, silent exam spaces, assignment extensions, and use of tech such as recorders, speech-to-text software... If you’re like I was and are worried that you’re asking too much asking for accommodations, remember two important things: 1) Accommodations exist to level the playing field, not to give us an edge, and 2) YOU PAY FOR THIS SERVICES. That huge, overwhelming tuition bill with all those “extra fees”? You’re paying for these services already, might as well take advantage of them!

Talk to your professors: This part is truly terrifying for me, but I’ve started opening up this semester to my professors and it has made a difference. The professor for my hardest class actually has a son with adhd so she understood and was even able to provide me with some resources that would help. At the very least, it made my professors aware of my struggles and aware that I wasn’t just being lazy, which calmed my RSD a bit.

Organization: Staying organized is important for any college student, but especially for those with adhd. We lose things a lot, and if things aren’t in obvious, constant places it becomes so much easier to lose or forget where we put things. That being said, your ‘organized’ will probably not be other peoples ‘organized’. For example, I use my Ipsy bags for organization. One holds any writing utensils, flashcards, and post-its, another holds anything medical-related, etc. It seems a bit cluttered and disorganized to other people but it works for me. So try keeping things in the same spot if possible, but remember that finding what organizational structures work for you might take time and effort. If your school has success coaching, I highly recommend it for this purpose! Which brings me to the next point.

Success Coaching: Most colleges offer some kind of program like this, though names may differ. Success Coaching is designed for students of any academic level in order to help them get and stay on track. My college offers study skills, schedule planning, test prep, time management, help navigating campus resources, and a whole host of others. And the people doing the coaching are usually grad students who’ve been through the process. They’re typically trained in working with students with adhd, because that tends to be a significant portion of their students. They’re also just really nice to talk to. Almost like a therapist, but not quite.

Really forgetful? The best thing you can do is change your environment, not try to change yourself. You probably won’t be able to stop your brain from forgetting your notebook at home, but you can get a five subject and keep it in your backpack at all times. Same with folders. Keep losing pens/pencils? Just get a fuckton and shove them in a pouch in your backpack in the beginning of the semester. I’m not kidding when I say I have at least 20 pens and pencils in mine, not including the glitter pens and highlighters. 

Planners: Many people have said that it will take time to find just the right planner for you, and they’re correct. The planner I use right now is 8x11 with wide boxes. Some prefer smaller planners, others will use planner apps or just the calendar in their phone. You’ll have to mess around a bit to see what works for you, but you do have options!

Printables: Oh man I love printables so much, but a lot of the time I find that they’re more trouble maintaining than my adhd can handle. You can find a ton on tumblr, free to download and print, and some very beautiful packs for sale on etsy. Right now I use a monthly budget printable and one for studying terms/definitions. Sometimes the adhd mind needs something pretty and different to cling to, so I try to switch things up every so often.

Color-coding: This absolutely will not work for everyone (I’ve seen people say color-coding notes gets the hung up on the coding and not the notes, and I can definitely see that happening). For me, I use color-coding in my planner. Each class gets its own color. This keeps me from seeing a page covered in the same color of ink or pencil and mentally blocking it out. Gelly roll has the most amazing glitter pens!

Test prep: Will vary depending on the person and how they learn best, but for me I’ve found that no one method will work on its own. I have class notes, typed notes, hand-written flashcards, flashcards on quizlet. I won’t pretend that it’s easy; it’s fuck-all time consuming and sometimes I don’t have energy for it, but depending on the class I usually need a combination of at least two different methods to work. This is definitely something success coaching can work with you to figure out!

General Life Advice (that will impact college):

Get on a sleep schedule: I don’t even care what your particular schedule is (because it’ll vary person to person) but just get on one. Much easier said than done, because our brains never want to shut up at night, but lack of a consistent sleep schedule will mess with your concentration, focus, hypersensitivity, etc. 

I’ll just do this later...: is the adhd monster talking. What even is later? Does it exist? Sometimes I have to tell myself “nope, we’re doing this right now!” Doesn’t always work, but I try my hardest to do things in the moment if executive dysfunction isn’t at my door.

Develop a support system: This can be difficult because sometimes making and maintaining friendships with adhd can be hard, and sometimes family members aren’t very receptive or supportive. But a strong support system can make all the difference in the world! If your current friends don’t understand the extent of what you’re dealing with, send some resources their way and you might be surprised how fast they get in your corner. But sometimes people without adhd just don’t get it. If your college has a meet-up for students with adhd like mine does, this is a great place to meet like-minded students who understand what you’re going through and can provide support and advice! 

I’m going to stop this here because it’s already too long, but I hope this is helpful to someone and I’d love it if you could add your own tips as well! 

[techtiger]

The Role Of Voice Recognition Technology In AI And Machine Learning.

Speech recognition technology is something that has been dreamed of and worked on for many decades.

From the beep-bopping of R2-D2 in Star Wars to Samantha's dissatisfied but charming voice, science fiction writers have played a big role in shaping expectations and predictions about how speech recognition will be in our world...

However, for all advances in modern technology, voice control is a very sophisticated relationship.

It is felt to be historically helplessly clear and nothing but a novelty to simplify our lives. That is until we start to get more into the field of big data, intensive learning, machine learning, and AI technology. Similarly, text to speech is a technology similar to voice recognition that converts digital text into voice. Text to speech technology makes computer to read text aloud from the text document. There are many best free text to speech software that you can use to let your device read for you without looking at the text.

Voice Recognition: A Brief History

As with any technology, what we know today comes from nowhere, someone and someone else.

The first recorded attempt at speech recognition technology was in 1,000 AD. However, the tool that can answer direct questions “yes” or “no” comes back through development.

Although the experiment does not technically involve voice processing in any form, the idea behind it must be part of the foundation of speech recognition technology: the use of natural language as an input to speed up the action.

Centuries later, Bell Laboratories worked to develop "Audrey", which could detect vowel-speaking numbers 1-9.

Later, IBM developed a device that could detect and distinguish 16 spoken words.

These successes have greatly enhanced the dominance of technology companies focusing on speech-related technologies. The Department of Defense also wanted to join the action. Researchers are working steadily toward the goal of making machines more capable of comprehending and responding to our verbal commands.

The history of speech recognition technology is long and winding. However, today’s speech systems such as Google Voice, Amazon Alexa, Microsoft Cortana, and Apple’s Siri are not where they are today, there are no early pioneers.

Thanks to the integration of new technologies such as cloud-based processing and ongoing data collection projects, these speech systems have improved the ability to constantly hear and understand a wide variety of words, languages ​​, and voices.

At this rate, the predictions of future writers are not as far-fetched as we might think.

The Voice Recognition Process: How Does It Work?

Around smartphones, smart cars, smart home appliances, voice assistants, and more, it's easy to know how speech recognition technology works.

Why?

Because it is easy to be misled by digital assistants. Speech recognition is still very complicated.

Think about how a child learns a language.

From day one, they hear the words used around them. Parents talk to their child, and even if the child does not respond, they perceive all kinds of sound signals; Noise, reflection, and pronunciation; Their brain designs and makes connections based on how their parents use their language.

Although it may seem difficult for humans to hear and understand, we train all our lives to develop this so-called natural ability.

Speech recognition technology essentially works the same way. Although humans have improved our process, we have yet to identify the best practices for computers. We must train them in the same way that our parents and teachers trained us. In addition, this type of training requires vision, research, and manpower.

These speech recognition systems take longer and more field data to complete; Thousands of languages, voices, and dialects need to be considered.

To say that we have not made progress; As of May 2017, Google's machine learning algorithm has now achieved a 95% word accuracy rate for the English language. This current rate is a limit to human accuracy, take care of yourself.

What is the best voice assistant?

So far, we have all heard and/or used speech recognition systems; They entered the technological ecosystem to become a means of communication between humans and technology.

Voice input is a more efficient form of computing, as Mary Meeker said in her annual Internet Trends report: Humans can speak an average of 150 words per minute, but can only type 40. Farewell texting and push buttons - we're so busy now bus.

What has become the dominant form of computing is that speech recognition is unbelievable. In addition to regional accents and speech impediments, background noise can make word recognition difficult. Not to mention multiple-voice input.

In other words, recognizing sounds alone is not enough.

These speech recognition systems must be able to distinguish between homophones (words that sound the same but mean something different), to distinguish proper names from separate words ("Tim Cook" is an individual, not merely a search request for a cook called Tim), and more.

Ultimately, speech recognition accuracy determines whether or not they become voice assistants. It certainly answers the question of which voice assistants are the best on the market right now; In terms of speech accuracy, innovation and usability, and compatibility with other smart systems.

Apple’s Siri

Apple's Siri was the first voice assistant launched by mainstream tech companies in 2011.

Since then, it has been integrated into all iPhones, iPods, Apple Watch, Homepod, Mac computers, and Apple TVs.

Through your phone, Siri is being used as a major user interface for automobiles and wireless AirPods earbuds in Apple's Carplay infotainment system.

With the release of Sirikit, a development tool that allows third-party companies to integrate with Siri and HomePod‌, Apple's initiative Intelligent Speaker (after the success of Amazon Echo and Google Home), voice assistant capabilities Become strong.

There is always Siri with you, whether on the road, at home or even literally on your body. This gives Apple a big advantage in terms of adoption.

Although Apple has a big head when it comes to Siri, many users are frustrated by the inability of the device to understand and execute voice commands.

Naturally, being as quick as possible means getting too many errors for a function that does not work as well as the function.

But, to this day Siri is notorious for misinterpreting voice orders, even by providing a list of nearby liquor stores to respond to requests for help with alcohol poisoning.

If you ask Siri to send you a text message or call on your behalf, it can be done easily. However, when it comes to communicating with third-party apps, Siri is slightly less powerful than its rivals, working with only six types of apps: ride-hailing and sharing; Message and call; Photo search; Payment; Fitness; And auto infotainment system.

Why?

Because Apple advises that "users should not use voice commands without human experience, and what can be done to ensure that Siri works well". Is ", Reuters reports.

Siri will open any ride service app on your iPhone and you can book on the go. Gives you options like traveling to the airport and ordering a car.

Focusing on the system capability of follow-up questions, language translation, and re-incorporation of Siri's voice into a more human-Esque will definitely help to iron out the voice assistant's user experience.

In addition, Apple controls its rivals by country in terms of availability and thus makes sense of the slang of a foreign accent. Siri is available in more than 30 countries and over 20 languages ​​- and, in some cases, many different dialects.

By comparison, Google Home is only available in seven countries and can only speak four languages ​​'simply' (English, German, French and Japanese), although it does support multiple versions of some languages. Alexa, on the other hand, can only handle English (U.S. and U.K.) and German.

Amazon Alexa

Inside Amazon's smash-hit Amazon Echo smart speakers, as well as the newly released Echo Show (voice-controlled tablet) and Echo Spot (voice-controlled alarm clock), Alexa is one of the most popular voice assistants today.

While Apple focuses on areas where it has the capacity and expertise to meet its needs, Amazon does not impose such restrictions on Alexa.

Instead, a voice assistant with a lot of "skills" (the term for applications on your Echo Assist devices) will "get the reliable following, even if they make occasional mistakes and are easy to use." Will try harder ".

Although some users have set Alexa's word recognition rate as a shadow behind other voice platforms, the good news is that Alexa will adapt to your voice over time with those with your unique voice or dialect. The problem can also be solved.

In terms of skills, Amazon's Alexa Skill Kit (ASK) probably pushed Alexa into a bonafide platform. ASK allows third-party developers to create applications and tap into Alexa's power without local support.

With over 30,000 skills and growing, Alexa has integrated Siri, Google Voice, and Cortana in terms of third-party integration. With the incentive to "add voice to your big ideas and more customers" (not to mention the ability to build for free in the cloud, "no coding knowledge required"), it's no surprise that developers are putting content on the skills platform. To

While some may not be able to help draw parallels with Apple's Appstore, it's catching the attention of developers trying to keep content - any content - on their platform regardless of whether it's worthwhile or not.

Its integration with smart home devices such as cameras, door locks, entertainment systems, lighting, and thermostats is another big selling point for Alexa.

Lastly, give users complete control over their home whether they are in bed or on the move. With Amazon's Smart Home Skill API (another third-party developer tool similar to ASK), you'll be able to control devices connected to customers from millions of Alexa-enabled endpoints.

When you ask Siri to add something to your shopping list, she adds it to your shopping list - without actually buying for you. Alexa goes one step further though.

If you ask Alexa to re-order her debris bags, she will go through Amazon and order them. You can order millions of Amazon products without lifting a finger; Natural and unique ability to surpass Alexa's rivals.

Microsoft’s Cortana

Based on the artificially intelligent role of the 26th century in the Halo video game series, Cortana launched in 2014 as part of Windows Phone 8.1, the next major update to Microsoft's mobile operating system.

At the end of 2017, Microsoft announced that its speech recognition system had reached an error rate of 5.1%. It surpassed the 5.9% error rate reached by a team of researchers from Microsoft Artificial Intelligence and Research in October 2016 and keeps its accuracy on par with professional human transcription, with benefits such as the ability to hear text multiple times.

In this race, every inch is important; When Microsoft announced its 5.9% accuracy rate at the end of 2016, they were ahead of Google. However, the fastest-moving year surpasses Google - but only 0.2%.

While percentages and accuracy rates are important, Cortana distinguishes itself from other voice assistants based on real, human-assisted assistants.

Rival services dig into data from devices, your search history, cookie trails you left on the Internet. While this is often useful, it can also be annoying in the form of non-stop notifications or it can scare the smart system into knowing too much about you.

We all saw 2001: the mother of all sensitive computers, the HAL 9000, was murdered with her pale red-eye and soft-butter robot voice.

To prevent this, Microsoft spoke with several high-level personal assistants, all of whom found that they had notebooks with important information about the person they were looking at. It was this simple idea that prompted Microsoft to create a virtual "notebook" for Cortana that would store personal information and anything Cortana approved for viewing and use.

It's not a privacy control panel, but it's exactly what Cortana does and gives you a little more control over what's not accessible.

For example, if you are not comfortable with Cortana accessing your email, you can add or remove access to your notebook. Another special feature? Cortana always asks you if she stores any information in her notebook.

Microsoft has teamed up with Halo developers on visual themes as well as voice actress Jane Taylor for Cortana's voice. These elements bring Cortana to life and form the personality and emotion to a system that would not have happened without that cooperation. Cortana’s personality shines through in everyday use - along with funny reactions from her circuit boards.

In addition to Google Assistant and Google Search, Cortana is supported by Microsoft's Bing search engine. This allows Cortana to chew up the data needed to answer your burning questions.

And, like Amazon, Microsoft has come up with its own home smart speaker, the Invoque, which performs many of the functions of its rival devices. As soon as Microsoft hits the market there is another big advantage - Cortana is available on all Windows computers and mobiles running Windows 10.

Google Assistant

One of the most common responses to a question these days is "LMGTFY". In other words, "Google me".

This only makes sense when Google Assistant talks about answering (and understanding) any questions.

From asking to translate a phrase into another language, to change the number of butter columns to one cup, Google Assistant not only provides the correct answer but also provides some additional context and source information for the website This suggests that Google's powerful search technology supports it, perhaps with a surprising exception.

Although Amazon's Alexa was released two years ago (via the Echo introduction) than Google Home, Google has made significant progress in capturing Alexa in a very short period of time. Google Home was released in late 2016, and within a year, it had already established itself as Alexa's most meaningful rival.

By the end of 2017, Google had stated a 95% word accuracy rate for American English; Currently the highest of all voice-assistants. It turns out to have a word error rate of 4.9% - Google is the first in the group to fall below the 5% limit.

While some have tried to strike back at Amazon, Google has released several similar products for Amazon. For example, Google Home is reminiscent of Amazon's Echo and Amazon Echo Dot's Google Home Mini.

Recently, Google announced some new, important partnerships with Lenovo, LG, and Sony to launch a series of assistant-powered "smart displays" that will once again resemble Amazon's Echo Show.

Nuance’s Dragon Assistant and Dragon Naturally Speaking.

Although Nance did not come with a smart home speaker, their Dragon Assistant, and Dragon natural speech systems have been used as the backbone of speech recognition for other technology companies. "I need to be able to talk without touching my phone," said Vlad Sejonha, chief technology officer at Nance Communications. "It's constantly listening for trigger words and pop up the calendar or create a text message or browser where you want to navigate".

Nance's voice-recognition technology is largely centered around speech systems in the car; Embedded dictation capability and bringing interactive information to the car.

“Another development involves a deeper level of understanding,” says Nance’s lead solution architect John West.

West argues, "Here, the goal is not just to identify speech, but to gather meaning and purpose that enables voice-driven systems to respond intelligently, in a way that meets the needs of the user."

What is the best voice assistant?

Here's what we know

With over 400 million devices using Google Assistant, including Google Home speakers and Android phones, the company's voice assistant is now installed on more than 400 million computers and devices.

Similarly, Microsoft has officially stated that Windows 10 has 400 million active users; Exclude mobiles running a single system.

Since Amazon’s Alexa is only available on their Echo speakers, this number will definitely reduce the number of dwarves competing against Alexa.

On the other hand, with over 300 million iPhones worldwide by mid-2001, Siri took advantage of this space - not to mention the number of people who owned an Apple Watch, MacBook, or iPad.

With the support of millions of pre-existing users for the tech giants mentioned above, a simple software update is needed to integrate their post-voice assistants worldwide.

For example, people with Google's Pixel phones will be part of the Google Ecosystem. They are more likely to invest in Google Home Speaker, so they can get entangled with YouTube, Google Search, Google Maps, and more. Apple, Amazon, and Microsoft users are the same, without the least repetition of what ecosystem and what products they spend on.

It may depend on the use case.

After all, there is no one-size-fits-all winner when it comes to voice assistants.

If you like the Apple-consumer, Siri and its wide distribution across all Apple products will help you.

If you want to make your home a smart home, Alexa already has thousands of software and hardware integrations ready.

If you've been looking for a helper who can answer all your weird and amazing questions, Google Assistant's search engine will find the rest. If you want a little more control over what information your digital assistant has access to, Microsoft's Cortana has that functionality.

Collaboration that sets the bar high

The recently announced partnership between Microsoft and Amazon on August 30, 2017, is the real deal-breaker here.

This is correct. Alexa and Cortana are officially working together. Since both companies do not have popular smartphones (unlike Google and Apple), they have changed their assistants to suit their strengths.

Users can say "Alexa, Open Cortana" on their Echo devices and "Open Cortana, Alexa" on their Windows 10 devices.

Alexa customers will be able to remember Cortana's special features, such as booking meetings or accessing work calendars, picking flowers, or read your work email on your way home.

Similarly, Cortana customers can ask Alexa to control their smart home devices, shop on Amazon.com, and communicate with more than 30,000 skills built by third-party developers.

Therefore, in terms of voice-activation and digital assistants leading this new industry, Amazon definitely takes the cake.

The company not only supports the creation of other voice-activated technologies through their ASK and Smart Home APIs, but they are also the original inventors to create a smart home speaker with a smart home speaker and screen.

In other words, they are moving faster (and moving forward) than their rivals, all of which are new by continuing to share.

Speech Recognition in-Car

Voice-activated devices and digital voice assistants not only make things easier.

It’s also about safety - at least when it comes to speech recognition in the car.

Companies like Apple, Google, and Nance are completely changing the driver experience in their vehicles; Allows drivers to focus on the road with the intention of eliminating the distraction of looking down on their mobile phones while they drive.

Instead of texting while driving, you can now tell who to call your car to or which restaurant to navigate.

Instead of scrolling through Apple Music to find your favorite playlist, you can ask Siri to find and play it for you.

If your car is running low on fuel, your speech system will not only let you know if your car needs refueling but also point to the nearest fuel station and ask if you have any specific brands. Priority to this

Or you can be warned that the petrol station of your choice is too far to reach with the rest of the fuel.

As advantageous as it may seem in the ideal scenario, speech technology in a car is dangerous if applied before high-speed accuracy. The study found that voice-activated technology in cars actually causes a higher level of cognitive distraction. This is because it is as new as technology; Engineers are still working on software kinks.

But, as rate speech recognition technology and artificial intelligence are improving, we can’t stay behind the wheel in a few years.

Speech Recognition Apps and Devices

Voice assistants are making a big difference in our personal lives, according to a recent study by Voice Labs that 30% of respondents cite smart home devices as the main reason for investing in Amazon Echo or Google Home.

This next generation of 'communication' technology provides users with a way to use the clumsy remote control interface.

Therefore, it allows consumers to talk and communicate with their electronics as they further increase the ease of human use and reduce the barrier to access to technology products.

Engineers must work hard to create an abundance of voice-controlled devices that can integrate with the voice technology of leading digital assistants; From appliances and safety devices to thermostats and alarm systems.

Nest, for example, is a company that invests capital in the new voice-technology frontier. “Your smart home should not be dumb,” the company said.

With the Nest Thermostat, you can use the Amazon Echo to control the temperature in your home with simple voice commands. Or, pre-order the Nest Hello Video Doorbell and get the Google Home Mini at no cost when shipping. From alarm systems to smoke and carbon monoxide alarms, Nest Protect thinks, speaks, and warns your device.

Bringing these voice assistants to the office in future applications of speech recognition, beyond the home.

In late 2017, Amazon announced new voice-activated tools for the office, hoping that verbal commands such as "Alexa, Print My Spreadsheet" would extend to normal office tasks. Microsoft's Cortana has begun to handle some other office tasks, such as scheduling meetings, recording meeting minutes, and arranging travel.

Today, only a handful of high-ranking officials have their own personal assistants. With the introduction of AI digital assistants in the workplace, everyone can be one.

To access the company's financial data from last week to last year, please ask your Google Assistant to create a graph showing the year's increase in click-through rates - there are many uses for implementing Digital-Assistant in the workplace.

Think about it - just like electronic computers, voice can go manually through the files on your computer so that paper records can be easily changed shortly before.

Video Games with Voice Control

In these use cases, speech recognition techniques have been implemented with the aim of simplifying our lives, which is also evolving in other areas. Namely, in the gaming industry.

Creating video games is already exceptionally difficult.

Plots, gameplay, character development, customizable gear, lottery systems, worlds, etc. can take years to display properly. Not only that, the game can change and adapt based on the actions of each player.

Now, imagine adding another level to gaming with Speech Recognition technology.

Many companies that create this idea do so with the intention of making gaming more accessible to those who are visually and/or physically challenged, as well as immersing players further in the gameplay by launching another layer of integration.

Voice control can reduce the learning curve for beginners, with less emphasis on recognizing controls; The player can start talking immediately.

In other words: it can now be very challenging for game developers to collect hundreds (if not thousands) of voice data, speech technology integration, testing, and coding to keep their international audience.

However, despite all the goals that tech companies are shooting and overcoming challenges, there are already video games that believe the benefits outweigh the barriers.

Even mobile games and apps are now capable of using voice-activation in addition to the classic console and PC versions. Seaman, starring Leonard Nimoy as a sarcastic man-fish, debuted in the late 1990s, and Mass Effect 3, released in 2012, is just the latest example of speech technology in video games.

What is our history, where are we going?

Speech recognition has made major advances in the last decade; it's been 1,000 years in the voice technology market. Magic eight ball to today.

The intense level of competition we see among these tech giants in the industry and the growing trend of companies creating materials in space indicates that we still have a long way to go.

[viralsoftllc]

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Camtasia 4

Camtasia 2020Developer(s)TechSmithInitial release28 October 2002; 18 years agoStable release(s)

Windows2021.0.0 / 27 April 2021; 2 days ago[1]macOS2021.0.0 / 27 April 2021; 2 days ago[2]

Operating systemWindows 10 1607 or later, macOS 10.15 or later[3]PredecessorCamtasia 2020TypeScreencasting and video editing softwareLicenseProprietaryWebsitewww.techsmith.com/video-editor.html

Camtasia 48khz

Camtasia 4 Serial

Free Camtasia 4 Download

The Camtasia TREC is a custom file container that holds more than just a video file. Other video editing software can't read or open a TREC file. The data contained in the TREC allows you to edit your video within Camtasia Studio 8.4 or Camtasia for Mac 2.8 after recording is complete. A TREC file may contain: AVI screen recording. Camtasia save as mp4 Camtasia is a powerful multifunctional video screen recording and video editing software developed by TechSmith with which you can freely dub voices into videos or add explanation and subtitles to your video file, and of course, there is much more functions to use. Techsmith Camtasia 2021 Review + Tutorial. Updated on May 5, 2021 By Rima Giri Leave a Comment Filed Under: Reviews. I recently had a black screen of death on my laptop. 4 GB of available disk space (Recommended SSD with 4GB of available disk space) Display dimensions of 1366 x 768 or greater (Recommended 1920 x 1080 or greater) Microsoft.NET 4.7.2 or later version (included) Dedicated Nvidia GeForce 10 series or newer video card (Recommended) USB or other external microphone for voice recording (Recommended).

Camtasia 48khz

Camtasia (/kæmˈteɪʒə/; formerly Camtasia Studio) is a software suite, created and published by TechSmith, for creating video tutorials and presentations directly via screencast, or via a direct recording plug-in to Microsoft PowerPoint. Audio or other multimedia recordings may be recorded at the same time or added separately from another source.

Major components[edit]

Camtasia consists of two major components:

Camtasia Recorder - a separate tool for capturing screen audio and video

Camtasia editor - the component for which the entire product is named, which is now a multimedia authoring tool with a 'timeline' interface for managing multiple clips in a stacked track form.

Camtasia Recorder[edit]

In Camtasia Recorder, users can start and stop recording with a hotkey combination at any time, at which point the recording can be halted and Camtasia Recorder can render the input that has been captured into a CAMREC format. The CAMREC file can be saved to disk or directly imported into the Camtasia component for editing. Camtasia Recorder allows audio recording while screen-capturing is in progress, so the presenter can capture live narration during a demonstration or presentation. Camtasia also supports dubbing in other audio tracks or voiceover during post-capture editing. Users may also download an add-in for Microsoft Power Point that will allow them to initiate recording of a presentation from within Power Point itself.

In Camtasia editor, multimedia objects of various formats can be imported into the clip library and arrange them in time order and stacked tracks using the timeline form of user controls. Overlays of various types may be added, including user-defined settings, such as when and how to display the cursor and pan-and-zoom effects such as the Ken Burns effect.

Post-production[edit]

After capturing a presentation in the Camtasia Recorder, the Camtasia component can be used to modify audio and video displayed as tracks by using the timeline control and object library interface with an integrated preview window. The image in the infobox to the right is a screen capture of the timeline interface. In addition, Camtasia allows automatic captions (speech-to-text), voice overlay for the presenter or editor, as well as the ability to add sound effects in various formats.

Rendering and deployment[edit]

The Camtasia program allows import of various types of multimedia video and audio files including MP4, MP3, WMV, WMA, AVI, WAV and other formats into the Camtasia proprietary CAMREC format, which is readable by Camtasia. The CAMREC format is a single container for various multimedia objects including video clips, still images, document screen shots and special effect containers. The created video can be exported to common video formats including MPEG-2, MPEG-4, WMV, AVI, and Adobe Flash.

Versions[edit]

VersionDateUpdate 1Update 28.0.0 for Windows19 June 2012v8.6.0 of 25 August 2015[1]9.0.011 October 20169.1.2 of 13 March 20189.1.5 of 7 May 20192018.0.019 June 20182018.0.8 of 7 May 20192019.0.030 April 20192020.0.028 April 20202021.0.027 April 2020[1][2]

Reviews[edit]

Camtasia's shortcomings noted in the PC World review of January 17, 2013 and CNET review of June 19, 2012 are as follows:

Camtasia 4 Serial

Rotation of objects is applied via a dialog rather than interactively, though many lower-priced video editors do provide interactive rotation and manipulation of objects such as text and video frames

Recording live from a DV camera is not supported

Still potentially overwhelming for the introductory user, tempered by the tutorial material available. NOTE the V8 release is a complete rewrite so much of the prior tutorial material written for the popular Camtasia v6 and v7 software for Microsoft Windows is not usable with this release.

Audio handling has minimal capabilities and no integration with other packages compared to some competitors in this price range

Lacks any video-clip manipulation or integration with other packages that have such capabilities

In 2005, PC World mentioned that Camtasia is 'powerful'.[4]

Free Camtasia 4 Download

In 2013, PC World published a 4 1/2 star review and noted Camtasia is a 'full-featured education/information video tool'.[5]

In 2012, CNET published a review and noted that Camtasia is a 'feature-packed screencast app' and 'does have a learning curve'.[6]

See also[edit]

References[edit]

^ abc'Camtasia (Windows) Version History'. TechSmith. 27 April 2021. Retrieved 27 April 2021.CS1 maint: discouraged parameter (link)

^ ab'Camtasia (Mac) Version History'. TechSmith. 27 April 2021. Retrieved 27 April 2021.CS1 maint: discouraged parameter (link)

^'System Requirements'. TechSmith. 3 September 2020. Archived from the original on 26 July 2017. Retrieved 3 September 2020.

^Bass, Steve (31 August 2005). 'Tips & Tweaks: Podcasts and Screencasts'. PC World. IDG. Retrieved 22 September 2020.CS1 maint: discouraged parameter (link)

^Wiener Grotta, Sally; Grotta, Daniel (17 January 2013). 'Review: Camtasia Studio 8 raises the bar on interactive video creation'. PC World. IDG. Retrieved 22 September 2020.CS1 maint: discouraged parameter (link)

^Parker, Jason (18 June 2012). 'Camtasia 8 vastly improves screencast frame rates'. CNET. CBS Interactive. Retrieved 22 September 2020.CS1 maint: discouraged parameter (link)

External links[edit]

Retrieved from 'https://en.wikipedia.org/w/index.php?title=Camtasia&oldid=1020210937'

Create, edit and produce stunning videos at any screen size. Use Camtasia to make tutorials, as well as a variety of training and marketing videos. Camtasia lets you edit and polish video of your computer screen and instantly share it to YouTube, portable devices and more. Create on-demand interactive training and support videos for instant viewing. Screencasts are perfect for rolling out new software, orienting new staff, showing customers how to use your product, or establishing a “self-help” desk. With Camtasia Studio’s flexible recording options, you can choose to capture full screen, window or region. Add in music tracks, microphone, your computer's audio, plus picture-in-picture with your video camera, and you've got a world-class screencast.

Download: Camtasia Studio 8.4.3 Build 1792 | 247 MB (Shareware) View: Homepage | Release Notes (not yet available)

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New Year Profit Bot Review – Features & Benefits

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[universitytranscriptions]

Automated Transcription - we test NCH Express Scribe and Temi

We get many people asking why we still transcribe manually, using (and paying) highly trained transcribers rather than just purchasing some voice recognition software that could convert speech to text in the same way that an iPhone can produce a dictated text message.  Manual Transcription - a throwback to the Stone Age? We always try to explain that whilst voice recognition software has come on in leaps and bounds in recent years and may work well for basic dictation, it is still nowhere near good enough for serious projects where there are more than one speaker and the interview environment is not perfect.  We haven’t tested automated transcription software for a while so we thought we should make sure that what we are telling people is still correct! Automated Transcription - The Test We have two interviews that we use for testing transcribers who apply for a role with us.  Both are two speaker interviews with no strong accents. One recording is crystal clear with no background noise, the other has a small amount of background noise from start to finish but the speech can still be heard quite easily above this noise.  The clear interview is very straightforward to transcribe and we expect all applicants to achieve 99-100% accuracy with this.  The interview with the background noise is nothing terribly difficult but does require more concentration to hear the words but all words can be heard clearly when listened to carefully.  Manual Transcription - 99-100% Accuracy Our experienced transcribers can transcribe this interview with 100% accuracy.  We expect new applicants to transcribe this interview with a minimum of 99% accuracy if they are to be offered a role. We feel this second interview is a good test for applicants because it replicates well the average interview that we receive from clients. Software - NCH Express Scribe & Temi For our test we decided to have both interviews transcribed using the most common home automated transcription software (NCH) and to upload both interviews to be transcribed by one of the most popular and highest rated online automated transcription services, Temi. Temi is a speech recognition company who say the following about themselves: "Temi is changing how people extract value out of their digital files. With the explosion of personal and online media, we believe there is tremendous value in this content, just waiting to be unlocked. We started building a better speech recognition service combined with user-friendly tools." Express Scribe uses the SAPI speech-to-text engine that is usually already installed on your computer if you are running Windows. If not, then Dragon Dictate or similar will be required. Automated Transcription Results Interview 1 - Clear and Crisp When we put the clear interview through the NCH Express Scribe automated speech to text the software got 40 words correct out of 598, which is an accuracy level of just under 7%. We were genuinely surprised at how poor the performance was from the NCH software as it produced a completely unusable document and that was with a crystal clear interview. When we uploaded the same interview with Temi they produced a transcription that had 466 words correct, which is just under 78% accurate.   Whilst being way below our manual transcription levels of 99% + accuracy for this interview, the Temi document was much better than the NCH results and could feasibly be used as a starting point for creating a useful transcription.  It is worth bearing in mind though that the Temi transcription was just one block of text so as well as having to make the corrections, it would need to be “knocked into shape” in terms of formatting and attributing text to particular speakers.  This would clearly become even more problematic with any additional speakers.   Interview 2 - Background Noise When we put the second interview with the clear speech but with background noise though both tests we got the following results.  NCH software got 7 words correct out of 598 which is an accuracy level of marginally over 1%.  Temi only got 25 words correct on this second interview which is an accuracy level of just above 4% and once more, just in one solid block of text.  We knew from the first test that NCH would not be able to transcribe this interview but we were genuinely very surprised at how badly Temi performed. Temi do say on their website that the service is unsuitable for recordings with background noise. As mentioned earlier, this interview is more challenging due to the background noise but every single word is audible above that background noise and accuracy levels of 98% and above are easily achievable by a competent transcriber.  Summary - Does Automated Transcription Work? In conclusion. The transcription software that you can use at home appears to still be all but useless for most serious transcription work.  NCH Express Scribe is not fit for purpose. Temi was much better. However the second interview we tried is very important to us when testing applicants for transcriber roles because although most of the work we receive has reasonably clear speech, it invariably has some form of background noise.  Not many of the interviews we receive are carried out in a silent environment.  This means that Temi would be of little or no use for the vast majority of work that comes into us. Temi is certainly useful for some transcription work, particularly single speaker dictation in a nice quiet environment. It is also possibly useful for the occasional short interview if carried out in a very quiet environment.  However,  given that in addition to having to carefully listen through the entire audio file to find and correct mistakes, one would also need to sort out the format of the document and attribute text to speakers, it is difficult to see that this would be particularly useful for anything but a one off interview.  AI transcription would certainly seem far too time consuming for anyone who has a number of interviews that need transcribing or who uses transcription services with any kind of regularity. Read the full article

[joeyrob1]

Hype on Deep Learning That No One Knows

Hype on Deep Learning That No One Knows

(2 votes, average: 5.00 out of 5)

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“Deep Learning is a new area of Machine learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence”.

The techniques developed from deep learning research during the last decade have impacted a broad range of signal and information processing work. It has widened scopes including key aspects of machine learning and artificial intelligence.

“Deep learning techniques are now being employed for all sorts of everyday tasks. Many of the big tech companies have their own AI divisions, and both Facebook and Google have launched efforts to open up their research by open sourcing some of their Software”.

Deep learning is a very broad field. It exceeds far ahead than the general perception that people have about Visual Recognition, Speech to Text or Natural Language Processing. It encompasses wide-ranging machine learning techniques, while making the best use of non-linear information which is hierarchical in nature. For a flavor of possibility, let us see the commercial uses of deep learning applications.

Agriculture: One would think of the role that deep learning has to play in the field of agriculture and farming. This modern era has replaced the traditional methods and has made the agriculture process and farming mechanized. Deep learning has introduced the concept of; Satellite Images for better management and improved response time, use of sensor data in order to have better farming techniques incorporated and learn from the past trends by analyzing series of data, and lastly the most important; the seed genetics as it helps to improve the quality of the crop analyzing the fertility of the soil. Deep Learning has eliminated the element of experiment by providing a set method of analysis and outcomes based on learning.

Finance: Over the last few decades, the modernization in the finance sector has been astonishing. Ledger books being replaced by amazing software while ensuring accuracy. Economic and financial Modeling has become a significant part for Government Institutes and International firms. These computer models have set a new standard in the field of deep learning. All you have to do is input a certain set of data into the neural network and just allow it to make predictions for the future, based on past trends. Deep Learning has taken it a step further with advancements in Time-series and Econometric Analysis. You just regress the data and you are all set for economic and financial forecasting.

Biology: Advancements in the field of medicine and biology have been truly revolutionary. Tremendous amounts of machine / statistical data used in research can be analyzed faster than ever. Machine Learning has increased the pace of medical discoveries, and at the same time has introduced life saving techniques. Discoveries in DNA, drugs and genetic modification have taken biological sciences to a whole new level.

Radiology: Medical imaging has made life easier for humans. Deep learning can be used to create heat maps on the medical images and to highlight the areas of interest. Just imagine the level of efficiency and accuracy in CT scans, MRI and ECG which can be attained through deep learning, and at the same time making the data set analysis in radiology even simpler.

Video Recognition: The amount of video data over the internet is massive. It might be required to make it discrete according to consumer preferences. Deep Learning facilitates with the help of algorithms to analyze and use the video better than ever before. Deep Learning has improved the analysis of security camera footage and in extracting the information from online videos.

Over the period of time, and depending on how deep learning techniques are intended to be used, it can be broadly categorized into three major classes.

Deep networks for unsupervised learning, are intended to capture high-order correlation of the visible data for analyzing the patterns when no information about target class labels is available. The “unsupervised feature” in literary terms refers to this class of the deep networks. While being used in the generative mode, this may also be intended to characterize joint statistical distributions of the visible data along with their associated classes when available and being treated as part of the visible data.

Deep networks for supervised learning, are anticipated to directly provide discriminative power for pattern classification purposes. This is done by characterizing the subsequent distributions of classes conditioned on the visible data. Target label data are always available in direct or indirect forms for such supervised learning. They are also called discriminative deep networks.

Hybrid deep networks, their main goal is discrimination which is assisted, often in a significant way, while using the outcomes of generative or unsupervised deep networks. This can be accomplished by better optimization of the deep networks in the previous category.

Deep learning has gained importance over the years. If we talk about the year 2006 and before that, deep learning and relevant architectures were unsuccessful. Primarily due to less investigations in this field. However, things have changed now. All thanks to;

Faster machines and more data helps DL more than other algorithms

New methods for unsupervised pre-training have been developed (Restricted Boltzmann Machines = RBMs, auto encoders, contrastive estimation, etc.)

More efficient parameter estimation methods

Better understanding of model regularization, ++

Since 2006, deep learning has set new records, often repeatedly, for almost every type of unsupervised data (that is, raw data without labels such as images, sound, time series, video and text). In many cases, the only algorithms that deep learning nets are competing with are themselves.

What can be better than having data driven medicine to support the existence of the human race, economic and financial performances to forecast state stability and getting desired information from clustered data. Deep Learning makes it all and much more possible.

Greater accuracy in classifying data enables us to make more informed decisions according to one’s own personal requirements. Deep learning delivers accuracy, but eventually it still does depend on us in making good decisions.

Brought to you by the RobustTechHouse team (A top app development company in Singapore).  If you like our articles, please also check out our Facebook page.

Hype on Deep Learning That No One Knows was originally published on RobustTechHouse - Mobile App Development Singapore

[tak4hir0]

AI Is Eating Software deepkapha.ai By Martijn van Attekum, Jie Mei and Tarry Singh Introduction Marc Andreessen famously said that “Software is eating the world” and everyone gushed into the room. This was as much a writing on the wall for many traditional enterprises as it was wonderful news for the software industry. Still no one actually understood what he meant.  To make his point he stated this example: "Today, the world’s largest bookseller, Amazon, is a software company �� its core capability is its amazing software engine for selling virtually everything online, no retail stores necessary. On top of that, while Borders was thrashing in the throes of impending bankruptcy, Amazon rearranged its web site to promote its Kindle digital books over physical books for the first time. Now even the books themselves are software." Marc Andreessen This was 2011.  Marc Andreessen TechCrunch Interestingly, Andreessen also said the following: "I, along with others, have been arguing the other side of the case...We believe that many of the prominent new Internet companies are building real, high-growth, high-margin, highly defensible businesses." Marc Andreessen (Read the full blog article at his a2z VC fund) Little did Andreessen envision that the same software industry could be at risk of being eaten. Fast forward to 2019 and the very same software industry is nervous. Very very nervous! And the reason is AI. Especially for those who haven’t bulked up their AI warchest.  Acceleration Wave (2009 - 2019) - When Software Started Eating the World Andreessen was right.  The companies that embraced software in 2011 are the current market leaders in their respective fields, and the top 5 market capitalization companies worldwide in the second quarter of 2019 are all offering some type of software solutions (ycharts.com).  Concurrently, the period since 2011 has shown an unprecedented growth in the developments in AI. Although several key ideas about AI have been around for long, a number of processes have accelerated their potential use. First, computing power, in particular for specialized AI chipsets, has vastly increased. Second, the amount of training data for AI algorithms is exploding with the advent of data lakes and a fully connected internet-of-things world, expanding AI domains and decreasing the costs to train algorithms. Third, a large number of technological bottlenecks (such as vanishing gradients) have been solved over the last few years, massively increasing accuracy and applicability of existing algorithms. Lastly, the decrease in costs for cloud storage and computing plus the facilitation of distributed collaborative working, made combining highly specialized knowledge easier than ever before.  The extent in which Andreessen’s cherished software companies are weaving AI into their products is however often limited. Instead, a new slew of start-ups now incorporates an infrastructure based around the above mentioned AI-facilitating processes from their very foundation.  HyperAcceleration Wave (2019 - 2030) - AI Has Started Eating Software Driven by an increase in efficiency, these new companies use AI to automate and optimize the very core processes of their business. As an example, no less than 148 start-ups are aiming to automate the very costly process of drug development in the pharmaceutical industry according to a recent update on BenchSci.  Likewise, AI start-ups in the transportation sector create value by optimizing shipments, thus vastly reducing the amount of empty or idle transports. Also, the process of software development itself is affected. AI-powered automatic code completion and generation tools such as TabNine, TypeSQL and BAYOU, are being created and made ready to use.  Let’s quickly look at a few example applications of this hyperacceleration wave: Automating the coding process by having TabNine autocomplete your code with AI! DeepTabNine Tabnine It is trained on around 2 million files from code repository GitHub. During training, its goal is to predict each token given the tokens that come before it. To achieve this goal, it learns complex behaviors, such as type inference in dynamically typed languages. Once Deep TabNine developers realized the parallel between code and natural language processing, they implemented the existing GPT-2 tool which uses the Transformer network architecture. The inventor of this tool is Jacob Jackson, an undergraduate student and ex-OpenAI intern who quickly realized this idea and created a software tool for it. Getting answers to any question about your medical data As AI will create the query to get the answer for you! Here, a group of medical researchers created a tool that you can ask literally any questions on medical data and the AI generates a customized SQL query that is then used to retrieve the relevant data from the database. Speech Text to Generating Database Query automatically Question to SQL Generation It's called Question-to-SQL generation. They used RNN (a form of deep learning, an AI on steroids for text analytics) with Attention and Point-Generator Network. For those more inclined to exploring the technical part of this feel free to read their research here and software code here. So is it time the armies of database administrators (DBAs) to go home? Creating a beautiful website based on your sketch While AI translates your sketch into code! Want to build your website quickly? All you need to do is sketch it and this platform will use AI to create software code like html, css and js code ready in vue.js instantly. Sketch to create a website with AI Zecoda Easy, huh? Just input your sketch and voila! your website pops out at the other end! Find out more about this platform here. These are just a few examples of how AI is increasingly encroaching all parts of software development and eliminating mundane tasks of coding and programming rapidly! This is due to the motivation to automate the process of numerical analysis, data collection and eventually, processing and relevant code production. Researchers have higher-than-ever awareness and knowledge to infiltrate each and every problem at all levels with AI-powered software, from day-to-day anecdotes such as: Which kind of cookies shall we recommend to a customer given their shopping preferences? To large-scale, manufacturer’s dilemma, for example: How do we automate the production line in an individualized yet systematic manner? And finally, to the processing of building smarter, easier-to-use software that may even write code for you. Apart from assisted decision making, diagnostic and prediction, work of AI researchers and influencers have led to a hyperacceleration wave: Software powered by AI does not only achieve performances comparable to the human level, but creates something that would challenge an average person’s imagination and perception of their own abilities. A person can no longer tell apart the fake celebrity faces generated by generative neural networks from the real ones, or need not remember the name of every function they will use when writing a script. Imaginably, the wide application domains and near-human performance of AI-powered software will cause a paradigm shift in the way people deal with their daily personal and professional problems. Although some of us are pessimistic about, or in some extreme cases, consciously avoiding a world with overwhelming AI-powered software, there is not so much room for an escape. Amazon, Google, and even your favorite neighborhood florist, are actively (and sometimes secretly) using AI to generate revenue. Face it, or be left behind.   What would you do if you were BMW today? "At this point, no one can reliably predict how quickly electromobility will progress, or which drive train will prevail... There is no customer requests for self driving BEVs. (electric vehicles)" CEO, BMW A classic trap most big enterprises with established business fall for is getting micro-focused on existing business segments while losing sight on the slowly eroding economic and business climate. Tesla's story as an electric car is known to all but many may not know that it is the self-driving feature and the heavy use of AI in both software and hardware where the secret sauce lies. They have already driven 10 billion electric miles and the cars are collecting all the more data to disrupt not just the automotive markets but its adjacent markets in manufacturing, servicing, sales and in general mobility. Tesla's AI is eating all other automotive industry's business. A few weeks later after his annual address, the BMW chief had resigned. CEO's and executives who however do wish to proactively adopt AI should do the following 5 things Concluding thoughts 1) Have your AIPlaybook Ready Last year I did a keynote panel together with a few industry peers and I was asked if AI could eat software and I said "Yes". Take a listen. Any company that is not in possession of its AI Playbook, that is not armed with data, algorithms and machine learning models, is certainly going to find itself in serious quandary. An example of an AI playbook is to assess your firm's maturity thoroughly and plan for ROI driven projects. AI Playbook deepkapha.ai 2) Upskill and/or hire a (good) data science team Upskilling your staff to be able to drive your AI transformation is the key to success for any organization aspiring to become an AI company. We've advised several large-scale data-intensive projects and here are a couple of key arguments that executives should take to heart. In a couple of years embracing AI is not a matter of trend riding, but survival; To survive an era in which AI is dominating both market and software, CEOs and executives need to level up their mindset for successful adoption and application of AI within their enterprise, for which they either have to upskill or find a good data science team; Know your game: A good team helps you understand how AI will make your company survive; Examples are abundant in the industry and it is key for companies to pay attention to latest trends and launch several smaller projects to extract out the key projects that can be industrialized at scale. 3) Develop Algorithms & Execute Your Data-Play From Day 1 Upgrading your technical infrastructure that can develop the latest AI algorithms, process large quantities of heterogenous datasets, build and train both industry benchmarked and novel AI models is an important first step. Once that is established it is very critical to develop meaningful dialog channels to envision and dream project ideas that are pain killers and dive directly into solving those problems with data. Finally, executing from Day 1 on the "good-enough" data models and algorithms is where a true AI company can define its momentum and gain sizeable lead from its nearest competition. 4) Implement a distributed knowledge structure As access to the right data is a key to valuable AI solutions, ensuring access to data generated or acquired within the company and outside will be of crucial importance. Following this realization, pharmaceutical companies are starting to create central repositories of the data gathered in their clinical trials. Consequently, their data science teams will have access to a structured knowledge database they can use to train AI algorithms.  A second way to ensure the distribution of knowledge, is to set up a distributed collaboration structure. With the advent of software mimicking group processes from setting schedules, having meetings, or doing a brainstorming session, integration of knowledge and expertise should no longer be limited by geographical location. 5) Tap into AI start-ups with relevant knowledge Andreessen’s example of Disney buying Pixar in order to stay relevant has paid off for Disney, which sold for over 8 billion dollar in movie tickets this year, making Disney the second biggest media company (Forbes). Yet the latest developments suggest AI could also optimize movie-making processes. Moreover, as Disney is creating a consumer platform with Disney+, AI might form the necessary basis to ensure optimal usage of the data generated by this platform. When not wanting to build data science teams from scratch, collaborating with or taking over relevant start-ups might again be necessary for companies such as Disney to stay competitive. So yes, AI has started eating software. What are you going to do? ___________________________________________________________ About contributing authors Martijn v Attekum MD (Oncology) and PhD Dr. Martijn Van Attekum (MD, PhD) works as a data scientist in biomedicine at the University of Cologne. He is an experienced project manager and writer, and is skilled in genomics, oncology, and machine learning. As Visiting AI Researcher at deepkapha.ai he participates in ground-breaking deep learning projects on medical image analysis. In his free time, he is very much attracted to everything the mountains have to offer, such as climbing, hiking, and mountain biking. Jie Mei PhD Computational Neuroscience Dr. Jie Mei is a computational neuroscience researcher who has completed her studies at the Ecole normale supérieure and Charité Universitätsmedizin Berlin. She is currently based in Edmonton, Canada and is responsible for the growth of AI research department within deepkapha.ai and its companies. Her research interests include computational neuroscience, neurorobotics, machine learning and data analytics in healthcare and medicine. She is also an active startup advisor.

[buddhajeans]

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A German band from the early 70’s changed the way music sound

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Kraftwerk was created in the German city Düsseldorf; the band formed by Ralf Hütter and Florian Schneider in 1970,  fronted by them until Schneider’s departure in 2008. Their signature is easily recognizable driving; repetitive rhythms with strong melodies, minimalist strictly electronic instruments, almost naïve lyrics simplified and at times sung through a vocoder of computer speech software. The harmonies are classical western; however, these simplified lyrics are conceptual and enormously strong future-oriented.

Description once exotic objects in our consumer culture that today are the most ordinary and important things surrounded with (similarities to pop art). In 1981 came the albums Computer Welt those lyrics singing about home computers, pocket calculators a conceptual work and vision of today’s world of computers. In 1986 came the albumElectric Café and again Kraftwerk lyrics are about the telephone, mobile phones, and a society builds upon electronic communication; still with the catchy melody laying on the top making their songs feel like any Beatles tunes sing along. Earlier work as the Autobahn (1974), Radioaktivität (1975) and Trans-Europe Expresss (1977) state a clear vision of the future, motorways, transportation, superfast trains, energy consumption etc.

No band has influenced pop culture more than Kraftwerk since the Beatles

In the 1970s and early 1980s, Kraftwerk distinctive sound was revolutionary and has had a lasting effect across many genres of modern music. No other band has influenced pop culture more than Kraftwerk since the Beatles, their massive impact on the sound and music for an artist such as Moby, David Bowie, R.E.M., Daft Punk, Orchestral Maneuver’s in the Dark, Madonna, Jay-Z, Kanye West, Missy Elliott and Fergie. It doesn’t stop their Techno music from Detroit would not have happened if it wasn’t the impact Kraftwerk had on ‘Belleville three’ (Juan Atkins, Kevin Saunderson & Derrick May), who fused the repetitive melodies of Kraftwerk with funk rhythms. Hip Hop roots is no exception for their influence; Trans Europe Express and Numbers mixed in Planet Rock by Afrika Bambaataa and The Soul Sonic Force, one of the earliest hip-hop/electro hits. Richard D James (Aphex Twin), Björk, Joy Division and New Order were heavily influenced by Kraftwerk. David Bowie’s “V-2 Schneider,” released as B-side to the “Heroes” single, features on the album “Heroes,” is a tribute to Florian Schneider. Furthermore, disco scene and later electronic music would not have been the same.

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Live at Tribal Gathering 1997

I have luckily seen the band play since the 80’s when I saw them at Rockefeller in Oslo, a 1000 capacity club, later the night. I even shared a few beers with Ralf Hütter and Florian Schneider on an after a show in a club near the venue. In 1997, I saw them on the legendary dance festival Tribal Gathering in Luton outside London. The performance should be one of the key concerts in their history; club land was at its highest point commercially and that night all other bands stopped playing simply because every other musician wanted to experience the band. Kraftwerk has always cultivated their own style, whatever trend going on in pop culture they resisted making changes; their total anti-fashion statement should turn to the fashion statement. After a concert, I had seen the members walk out of a venue without even being recognized, with a small sack, jeans and a jacket they looked like the most ordinary people.

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The album The Man-Machine (German: Die Mensch Maschine), was released in 1978, and it is the album that created the fashion look this post is about. The album was recorded at their studio Kling Klang; however, due to the complexity of the recording, the album was mixed at Studio Rudas in Düsseldorf. The cover of the album produced in white, red and black and the design was highly inspired by the Russian artist El Lissitzky, and the moment named Suprematism. The cover shows the band members dressed in red shirts and black ties. Great website on Kraftwerk publications etc.

The Man Machine

The tune from the album Das Model or “The Model should become one of the most selling records in Kraftwerk history, and the song is also a classic tune for the dance floor. Many of Kraftwerk cover art designed by German multi-artist and painter Emil Schult, his unique signature style highlighting his role in pioneering the unique aesthetic that eventually came to represent not just Kraftwerk, but an entire style ethos of the period, copied and admired still today. Schult style can remind of Russian communist propaganda posters; however, on acid as many of his paintings shows a dream of space or even an urge to break out of the strict frame of the design.

On 21 November 2008, Kraftwerk officially confirmed Florian Schneider’s departure from the band; Floridan is one of the original members from the start. Kraftwerk has not only a pioneer electronic music but pushed the limits of music technology with some notable innovations, such as custom-built devices and self-made instruments. The Kling Klang studio has always been perceived as a complex music instrument as well as a sound laboratory; especially Florian Schneider developed a fascination for music technology, sponsored by computer brands as IBM and Sony. Donatella Versace used the theme of Kraftwerk “The Man-Machine” in their menswear line to create a contemporary spin. Alexandre Plokhov head of menswear at Versace, he ushered in a new skinny tailored silhouette. Lean black suits were worn with high-necked red shirts or T-shirts for a look that channeled the German band Kraftwerk.

 Immortalized

Kraftwerk was immortalized when they were performing eight shows at the Museum of Modern Art April 10th through April 17th, 2012 and Tate Modern, the concert sold out so fast the ShowClix servers crashed. I guess almost every single artist was visiting MoMA or Tate Modern for one or more Kraftwerk concerts; from REM’s Michael Stipe, shipping scion Stavros Niarchos and curator Vito Schnabel, consisted mainly of male hipsters, art types and electronic enthusiasts in a series of concerts understood as “a visual and phonic feast. Kraftwerk finally released The Catalogue box set on 16 November 2009, a 12? LP-sized box set containing all eight mastered CDs in cardboard slipcases, as well as LP-sized booklets of photographs and artwork for each individual album.

KRAFTWERK MUSIC NON-STOP

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WHO: Kraftwerk WHERE: Düsseldorf, North Rhine-Westphalia, Germany GENRES: Krautrock, avant-garde, EDM, experimental, synthpop ESTABLISHED: 1970 –present MEMBERS: Ralf Hütter – lead vocals, vocoder, synthesizers, keyboards, organ, drums, and percussion, guitar, bass guitar (1970–1971, 1971–present) Fritz Hilpert – electronic percussion, sound engineering (1987

SONGS ON MAN MACHINE

The Robots, Die Roboter

Spacelab

Metropolis

The Model, Das Modell

Neon Lights, Neonlicht

The Man-Machine, Die Mensch-Maschine

DISCOGRAPHY

Kraftwerk (1970)

Kraftwerk 2 (1972)

Ralf und Florian (1973)

Autobahn (1974)

Radioaktivität (1975)

Trans-Europe Express (1977)

Die Mensch-Maschine (1978)

Computerwelt (1981)

Electric Café (1986)

BANDS AND ARTISTS INFLUENCED BY KRAFTWERK

Moby

David Bowie

Daft Punk

Orchestral Maneuver’s in the Dark

Madonna

Jay-Z

Kanye West

Missy Elliott and Fergie

U2, Neon lights

Laibach’s

Uwe Schmidt Senor Coconut,

Dr. Alex Paterson the Orb

Afrika Bambaataa Planet Rock

Simple Minds, Neon lights

Ladytron

Yazoo

Depeche Mode

Franz Ferdinand

Coldplay, Talk

Official website of Kraftwerk  www.kraftwerk.com

kraftwerk records for sale on recyclesound.com

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The Model Computer love Vinyl 7 Inch

Tribal Gathering CD compilation live

Radio-Aktivität LP vinyl

Man-Machine LP vinyl Fame

Tour de France Vinyl 12 inch

Expo remix 2×12 vinyl

Electric Cafe Vinyl Album

Das Model EP 12 vinyl

Showroom dummies EP 12 vinyl

The Mix 2xLP vinyl (German Version)

Expo2000 EP 12 vinyl

Showroom dummies Single 7 vinyl

Computer love Single 7 vinyl

The Model, Single 7 vinyl

Pocket calculator Single 7 yellow vinyl

Pocket calculator Single 7 vinyl

Die Roboter Single 7 vinyl

Kraftwerk changed music, youth culture and fashion A German band from the early 70’s changed the way music sound Kraftwerk was created in the German city Düsseldorf; the band formed by…

[cloudbusterpress]

What it’s like to be a speechwriter

Do you have a gift for knowing what people are trying to say, and how to help them say it so they shine? Do you enjoy researching topics, and have an ability to encapsulate that research into a clear message? Is the persuasive essay your favorite assignment in English class? If so, scroll down to read more about speechwriting from a professional in the field, former speechwriter Rob Costello. And check out all the other cool careers in writing profiled on TIPS FOR TEEN WRITERS!

How did you get started as a speechwriter?

I never set out to become a speechwriter. In fact, when I was a teenager I didn’t really set out to be much of anything. I graduated high school not having a clue what I wanted to do with my life, and for most of my 20s I worked in a series of low-skill, low-wage jobs. I cleaned toilets and flipped burgers. I dealt cards in a casino. I processed trade documents for an international bank.

When I met my future husband, I moved to Ithaca, NY to be with him. There I got a job dispatching police and emergency services for the Cornell University Police Department. What a crazy, intense job that turned out to be! I quickly realized answering 911 calls all day long was way too stressful for me, and so after only a year of doing that, I managed to snag another job at Cornell that was much more my speed: receptionist in the Dean’s Office of the College of Agriculture and Life Sciences (CALS).

This is where I spent the next decade, working my way up from receptionist, to the dean’s administrative assistant, and finally to her executive assistant and chief of staff, where I helped her run the college. I enjoyed this experience very much. CALS is one of the leading ag and life sciences research institutions in the world. Working for the dean, I got to learn a great deal about the cutting-edge environmental, biological, and food systems research happening in the college. I also met tons of interesting people, from Nobel prize-winning scientists and Fortune 500 CEOs, to senators and members of Congress, and some of the brightest, most dedicated students in the world. Finally, I learned the ins and outs of what it takes to run a world-class research and academic institution with well over a thousand faculty and employees, and an annual budget in the hundreds of millions of dollars.

It was during this period that I first realized I could make a career out of writing. A big part of my job was helping the dean manage the huge volume of correspondence she received, literally hundreds of letters and emails a day. Because she couldn’t possibly answer all of these messages herself, I often drafted responses in “her voice,” which she would then review, edit, and sign. I’d always loved to write, and over time this became my favorite part of the job.

Eventually, I went back to school, earning my bachelors degree in English and an MFA in writing for children and young adults, while still working full-time (something I don’t recommend if you can possibly avoid it). When the position of the dean’s speechwriter became available, my educational background, extensive  knowledge of the college, and deep familiarity with the “dean’s voice” made me uniquely qualified for the job.

What is a typical day like?

It’s hard for me to pin down what a typical day as a speechwriter was like, because speechwriting was only half of my job. At the same time, I was also the college’s social media manager, which meant I ran CALS’ Twitter, Facebook, Instagram, Tumblr, and YouTube platforms, and wrote articles for various college publications. Depending on the dean’s public speaking schedule, which varied widely throughout the year, I could spend as much as 80% of my time working on speeches or as little as none.

That said, when I left CALS a few years ago to pursue fiction writing and teaching full-time, the dean was giving anywhere from 90 to 120 public addresses a year, which breaks downs to something like two to three speeches a week. Of course, not all speeches are created equal, and many of these were brief remarks that required minimal research and preparation.

On the other hand, some of the major speeches, such as the annual State of the College address, could take weeks to prepare. These involved massive amounts of research and data collection, interviewing faculty about new college initiatives, reviewing financial and budgetary reports with college officers, creating graphs and gathering photographs for slide presentations, familiarizing myself with the venue and A/V equipment that would be used for the speech, and then finally crafting the speech, followed by multiple rounds of revision with the dean.

In general, when I was working on a major address like this, most of my day was spent at my desk in front of my computer, doing research, drafting the text, and preparing the slides.

What training, education or preparation would help someone to be a good speechwriter?

To be honest, the most important training I received came from my high school English teachers, who taught me how to write a persuasive essay. When you reduce them to their essence, most speeches are merely persuasive arguments read aloud. They begin with an introduction that leads to a thesis statement, followed by a series of supporting points that build to a summary conclusion. Since I was also active in speech and debate as a teen, I had experience crafting arguments about complicated issues that were accessible and easy to convey while speaking. Who knew the basic skills I learned in high school would turn out to be so important to my job years later?

In college, I did coursework in speechwriting, presentation making, and rhetoric that was all very valuable, too.

Finally, all those years working in the dean’s office furnished me with a wealth of knowledge and resources that proved invaluable to my speechwriting career. Having a basic understanding of the different kinds of scientific research conducted in the college was crucial, because so many of the dean’s speeches involved promoting that work to alumni, politicians, and other stakeholders. It also really helped that I’d become something of an expert on the institution of CALS itself. This meant I always knew just whom to ask to get my questions answered quickly and accurately. Furthermore, because I was so familiar with the college’s inner workings, I understood many of the complicated subjects the dean spoke about, such as the budget and various policies and initiatives. This enabled me to craft speeches without a lot of coaching that were coherent and authoritative on these complex matters. I can’t imagine how hard it would have been for me had I not spent so many years beforehand getting to know the dean and the college so well.

Of course, this experience was unique to me and my job in CALS. But generally speaking, I think for any aspiring speechwriter the lesson here is to become as much of an expert as you possibly can on the subjects you will be writing about. Do your research. Ask questions. Be curious. Learn as much as you can before you ever sit down to write, because all of that knowledge will lend your speeches clarity and authority.

What skills do you think helped you do the job of speechwriting well?

Writing well persuasively is the most important skill to master. Knowing how to frame an argument and anticipate counterarguments is a big part of this, as well as being able to translate complicated issues or ideas into simple, clear, compelling language. Listening is also an essential skill, as well as being able to take critical feedback. Time management and organizational skills are invaluable, especially when multiple deadlines loom. Basic research, journalism, and interviewing skills are also extremely useful. Being comfortable setting up and troubleshooting A/V equipment is important, as is proficiency with presentation and graphics software like PowerPoint, Prezi, InDesign, and Keynote.

What type of person would be a good fit to be a speechwriter?

Somebody who is tenacious about getting the facts right. Somebody who enjoys writing persuasively and changing people’s minds with words. Somebody who doesn’t seek the spotlight and who doesn’t mind having another person receive the glory for what they’ve written. Somebody who cares passionately about the agenda being pursued by the person or organization they work for. (For example, it’s probably not a great idea if you’re an environmentalist to take a job writing speeches for the President of Exxon!)

What are the down sides of speechwriting?

You spend most of your time alone at a desk! It can be a challenge to find a good speechwriting job. Your job satisfaction is often dependent on whether or not you are able to satisfy one person (the person giving the speeches), so if you have a difficult or demanding boss, it can make your life a real drag.

What are the up sides of speechwriting?

Speechwriting is a great job for an introvert! It’s also tremendously rewarding to be able to work with an influential leader to craft a speech that may change people’s minds and influence lives. In my time at CALS, I worked on several major addresses the dean gave about the environment, education, and the value of scientific research in promoting a better world, all issues I care deeply about. Speechwriting gave me the opportunity to feel that I was contributing to the academic and scientific mission of the college, without actually being an academic or a scientist. Speechwriters can often play an important role in helping to spread the word about important issues and ideas. If you care about things like politics and activism, but aren’t the kind of person who can get up in front of others and lead, being the one behind the scenes who helps those leaders be more effective in communicating their messages can be extremely empowering and satisfying.

What resources, professional journals, organizations or social media sites keep you informed about your industry?

Unfortunately, I’ve been away from speechwriting for a while now, so I haven’t kept up with current resources. However, I do know that the Professional Speechwriters Association was founded in 2013 and offers information and links to non-members on their website.

Any words of advice for people interested in speechwriting?

I think it’s most important to develop a good rapport with the person you’re writing speeches for. After all, you are essentially putting words into their mouth. Words they will be speaking in public. Words they may be judged on and/or criticized for later on. By the very nature of the job, speechwriters are often working for influential public figures, such as politicians and other leaders. It can be a strangely intimate experience to see these powerful people with their guard down, expressing fears, anxieties, and vulnerabilities that don’t always correspond to their well-honed public images. It’s important, therefore, that you earn their trust by doing everything you possibly can to make their job easier. This means listening to how they speak, their unique speech patterns, vocabulary choices, and sentence structure. It means familiarizing yourself with the kinds of jokes and anecdotes they’re comfortable telling, as well as the subjects they wish to avoid. It means being scrupulously well-prepared and always having your facts straight, so that they are not embarrassed by giving out bad information or saying something inadvertently offensive or disrespectful to their audience. Finally, it means understanding what’s most important to them about the speech they are giving, what their goals are for it, and what message(s) they are trying to convey. After all, it isn’t about you and your pretty words. Your number one priority is to make sure they shine!

Rob Costello writes fiction for and about queer youth. He holds an MFA in Writing from the Writing for Children and Young Adults Program at the Vermont College of Fine Arts. An alumnus of the Millay Colony for the Arts and the New York State Summer Writers Institute, his short fiction has appeared in Hunger Mountain, Stone Canoe, Eclectica, and Narrative, and is forthcoming in Rural Voices: YA Stories of Growing Up in Remote Communities (Candlewick, Fall 2020). He teaches creative writing to teens and adults, and has been on the faculty of the Whole Novel Workshop at the Highlights Foundation since 2014. He recently finished work on his debut young adult novel entitled An Ugly World for Beautiful Boys, and lives with his husband and various four-legged companions on top of a wide and windy hill in upstate NY.

Find out more at www.cloudbusterpress.com.

[sciforce]

A Comprehensive Guide to Natural Language Generation

As long as Artificial Intelligence helps us to get more out of the natural language, we see more tasks and fields mushrooming at the intersection of AI and linguistics. In one of our previous articles, we discussed the difference between Natural Language Processing and Natural Language Understanding. Both fields, however, have natural languages as input. At the same time, the urge to establish two-way communication with computers has lead to the emergence of a separate subcategory of tasks dealing with producing (quasi)-natural speech. This subcategory, called Natural Language Generation will be the focus of this blog post.

What is NLG?

Natural Language Generation, as defined by Artificial Intelligence: Natural Language Processing Fundamentals, is the “process of producing meaningful phrases and sentences in the form of natural language.” In its essence, it automatically generates narratives that describe, summarize or explain input structured data in a human-like manner at the speed of thousands of pages per second.

However, while NLG software can write, it can’t read. The part of NLP that reads human language and turns its unstructured data into structured data understandable to computers is called Natural Language Understanding.

In general terms, NLG (Natural Language Generation) and NLU (Natural Language Understanding) are subsections of a more general NLP domain that encompasses all software which interprets or produces human language, in either spoken or written form:

NLU takes up the understanding of the data based on grammar, the context in which it was said and decide on intent and entities.

NLP converts a text into structured data.

NLG generates a text based on structured data.

Major applications of NLG

NLG makes data universally understandable making the writing of data-driven financial reports, product descriptions, meeting memos, and more much easier and faster. Ideally, it can take the burden of summarizing the data from analysts to automatically write reports that would be tailored to the audience.The main practical present-day applications of NLG are, therefore, connected with writing analysis or communicating necessary information to customers:

Practical Applications of NLG

At the same time, NLG has more theoretical applications that make it a valuable tool not only in Computer Science and Engineering, but also in Cognitive Science and Psycholinguistics. These include:

NLG Applications in Theoretical Research

Evolution of NLG Design and Architecture

In the attempts to mimic human speech, NLG systems used different methods and tricks to adapt their writing style, tone and structure according to the audience, the context and purpose of the narrative. In 2000 Reiter and Dale pipelined NLG architecture distinguishing three stages in the NLG process:

1. Document planning: deciding what is to be said and creating an abstract document that outlines the structure of the information to be presented.

2. Microplanning: generation of referring expressions, word choice, and aggregation to flesh out the document specifications.

3.Realisation: converting the abstract document specifications to a real text, using domain knowledge about syntax, morphology, etc.

Three Stages of the NLG Process

This pipeline shows the milestones of natural language generation, however, specific steps and approaches, as well as the models used, can vary significantly with the technology development.

There are two major approaches to language generation: using templates and dynamic creation of documents. While only the latter is considered to be “real” NLG, there was a long and multistage way from basic straightforward templates to the state-of-the-art and each new approach expanded functionality and added linguistic capacities:

Simple Gap-Filling Approach

One of the oldest approaches is a simple fill-in-the-gap template system. In texts that have a predefined structure and need just a small amount of data to be filled in, this approach can automatically fill in such gaps with data retrieved from a spreadsheet row, database table entry, etc. In principle, you can vary certain aspects of the text: for example, you can decide whether to spell numbers or leave them as is, this approach is quite limited in its use and is not considered to be “real” NLG.

Scripts or Rules-Producing Text

Basic gap-filling systems were expanded with general-purpose programming constructs via a scripting language or by using business rules. The scripting approach, such as using web templating languages, embeds a template inside a general-purpose scripting language, so it allows for complex conditionals, loops, access to code libraries, etc. Business rule approaches, which are adopted by most document composition tools, work similarly, but focus on writing business rules rather than scripts. Though more powerful than straightforward gap filling, such systems still lack linguistic capabilities and cannot reliably generate complex high-quality texts.

Word-Level Grammatical Functions

A logical development of template-based systems was adding word-level grammatical functions to deal with morphology, morphophonology, and orthography as well as to handle possible exceptions. These functions made it easier to generate grammatically correct texts and to write complex template systems.

Dynamic Sentence Generation

Finally taking a step from template-based approaches to dynamic NLG, this approach dynamically creates sentences from representations of the meaning to be conveyed by the sentence and/or its desired linguistic structure. Dynamic creation means that the system can do sensible things in unusual cases, without needing the developer to explicitly write code for every boundary case. It also allows the system to linguistically “optimise” sentences in a number of ways, including reference, aggregation, ordering, and connectives.

Dynamic Document Creation

While dynamic sentence generation works at a certain “micro-level”, the “macro-writing” task produces a document which is relevant and useful to its readers, and also well-structured as a narrative. How it is done depends on the goal of the text. For example, a piece of persuasive writing may be based on models of argumentation and behavior change to mimic human rhetoric; and a text that summarizes data for business intelligence may be based on an analysis of key factors that influence the decision.

NLG Models

Even after NLG shifted from templates to dynamic generation of sentences, it took the technology years of experimenting to achieve satisfactory results. As a part of NLP and, more generally, AI, natural language generation relies on a number of algorithms that address certain problems of creating human-like texts:

Markov chain

The Markov chain was one of the first algorithms used for language generation. This model predicts the next word in the sentence by using the current word and considering the relationship between each unique word to calculate the probability of the next word. In fact, you have seen them a lot in earlier versions of the smartphone keyboard where they were used to generate suggestions for the next word in the sentence.

Recurrent neural network (RNN)

Neural networks are models that try to mimic the operation of the human brain. RNNs pass each item of the sequence through a feedforward network and use the output of the model as input to the next item in the sequence, allowing the information in the previous step to be stored. In each iteration, the model stores the previous words encountered in its memory and calculates the probability of the next word. For each word in the dictionary, the model assigns a probability based on the previous word, selects the word with the highest probability and stores it in memory. RNN’s “memory” makes this model ideal for language generation because it can remember the background of the conversation at any time. However, as the length of the sequence increases, RNNs cannot store words that were encountered remotely in the sentence and makes predictions based on only the most recent word. Due to this limitation, RNNs are unable to produce coherent long sentences.

LSTM

To address the problem of long-range dependencies, a variant of RNN called Long short-term memory (LSTM) was introduced. Though similar to RNN, LSTM models include a four-layer neural network. The LSTM consists of four parts: the unit, the input door, the output door and the forgotten door. These allow the RNN to remember or forget words at any time interval by adjusting the information flow of the unit. When a period is encountered, the Forgotten Gate recognizes that the context of the sentence may change and can ignore the current unit state information. This allows the network to selectively track only relevant information while also minimizing the disappearing gradient problem, which allows the model to remember information over a longer period of time.

Still, the capacity of the LSTM memory is limited to a few hundred words due to their inherently complex sequential paths from the previous unit to the current unit. The same complexity results in high computational requirements that make LSTM difficult to train or parallelize.

Transformer

A relatively new model was first introduced in the 2017 Google paper “Attention is all you need”, which proposes a new method called “self-attention mechanism.” The Transformer consists of a stack of encoders for processing inputs of any length and another set of decoders to output the generated sentences. In contrast to LSTM, the Transformer performs only a small, constant number of steps, while applying a self-attention mechanism that directly simulates the relationship between all words in a sentence. Unlike previous models, the Transformer uses the representation of all words in context without having to compress all the information into a single fixed-length representation that allows the system to handle longer sentences without the skyrocketing of computational requirements.

One of the most famous examples of the Transformer for language generation is OpenAI, their GPT-2 language model. The model learns to predict the next word in a sentence by focusing on words that were previously seen in the model and related to predicting the next word. A more recent upgrade by Google, the Transformers two-way encoder representation (BERT) provides the most advanced results for various NLP tasks.

NLG Tools

You can see that natural language generation is a complicated task that needs to take into account multiple aspects of language, including its structure, grammar, word usage and perception. Luckily, you probably won’t build the whole NLG system from scratch as the market offers multiple ready-to-use tools, both commercial and open-source.

Commercial NLG Tools

Arria NLG PLC is believed to be one of the global leaders in NLG technologies and tools and can boast the most advanced NLG engine and reports generated by NLG narratives. The company has patented NLG technologies available for use via Arria NLG platform.

AX Semantics: offers eCommerce, journalistic and data reporting (e.g. BI or financial reporting) NLG services for over 100 languages. It is a developer-friendly product that uses AI and machine learning to train the platform’s NLP engine.

Yseop is known for its smart customer experience across platforms like mobile, online or face-to-face. From the NLG perspective, it offers Compose that can be consumed on-premises, in the cloud or as a service, and offers Savvy, a plug-in for Excel and other analytics platforms.Quill by Narrative Science is an NLG platform powered by advanced NLG. Quill converts data to human-intelligent narratives by developing a story, analysing it and extracting the required amount of data from it.

Wordsmith by Automated Insights is an NLG engine that works chiefly in the sphere of advanced template-based approaches. It allows users to convert data into text in any format or scale. Wordsmith also provides a plethora of language options for data conversion.

Open-Source NLG Tools

Simplenlg is probably the most widely used open-source realiser, especially by system-builders. It is an open-source Java API for NLG written by the founder of Arria. It has the least functionality but also is the easiest to use and best documented.

NaturalOWL is an open-source toolkit which can be used to generate descriptions of OWL classes and individuals to configure an NLG framework to specific needs, without doing much programming.

Conclusion

NLG capabilities have become the de facto option as analytical platforms try to democratize data analytics and help anyone understand their data. Close to human narratives automatically explain insights that otherwise could be lost in tables, charts, and graphs via natural language and act as a companion throughout the data discovery process. Besides, NLG coupled with NLP are the core of chatbots and other automated chats and assistants that provide us with everyday support.

As NLG continues to evolve, it will become more diversified and will provide effective communication between us and computers in a natural fashion that many SciFi writers dreamed of in their books.

[zanytimetravelenthusiast-blog]

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4 Resume Writing Principles Every Student Should Know

1. Literacy

Of course, for many works one hundred percent literacy is not required. Experience shows that grammatical and speech errors are weakly related to the business and strong-willed qualities of a candidate - practical skills, efficiency, purposefulness, organizational streak, ability to achieve results.

But errors often indicate the level of preparation of a candidate as a specialist - about his erudition, theoretical training, logical and algorithmic abilities, ability to clearly and coherently express his thoughts.

In any case, grammatical errors have never yet contributed to a good perception of the text and did not improve the quality of the resume. Ask familiar philologists to read your resume before you decide to send it.

The same applies to a resume written in a foreign language. Do not use automatic translation software! They are still working so badly that they are unsuitable for anything serious. The result will cause laughter and misunderstanding.

2. Structure

Do not write a coherent text at all. Do not make a resume into a literary work! It's very inconvenient to work with him.

Managers are busy people and usually read a summary, as they say, diagonally, snatching out the places and keywords they need. Therefore, the resume should be structured.

Each section should be formalized - either reduced to a table (track record, education), or each new element (name, address, etc.) start with a new line. It is not necessary to draw borders and dividing lines of tables - it is enough if the text will be located quite strictly on the columns and well structured.

Write headings in large print so that the eye easily snatches the necessary information. Do not abuse the small elements of the design - italic, bold, underline, words from capital letters.

You can greatly facilitate the work with the structure if you use resume builder tools. They turn your text into a ready-made template and save your time. Check curriculum vitae apps to find the best ones.

3. More facts

Only facts should be described in detail, avoiding flattery self-assessments like "great work experience", "teamwork skills", "good organizational skills", etc.

Let the facts speak for you. So, from the track record you should see how much time you had to manage the group, department, enterprise, how many people were in charge, what complex tasks you had to perform, what awards and rewards you received.

4. No false modesty

In no event should the important facts for the employer be omitted. This not only worsens the quality of the resume, but also - if it reveals concealment of important facts during the interview - it undermines the credibility of the resume text and the candidate himself.

It does not matter whether the positive fact is hidden or negative. As noted above, the real modesty is not to assess yourself.

Let others do this on the basis of carefully selected and correctly presented facts of your work biography.

Shyness and false modesty inherent in many people do not adorn, but demeans all participants in the process of hiring. Your task is to provide all the necessary information about yourself - so that there are no additional questions or assumptions that you are hiding something.