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Voice to Text Solutions

Full, Balanced Reviews of All the Voice to Text Options on the Market

Welcome to VoicetoText.me! We’ve got you covered with all the information you need to know on different voice to text solutions. Look out for answers to the following questions:

  • Which voice to text solution is best?
  • How accurate are voice to text software, really?
  • How does voice to text even work?

Below you’ll find information and links to articles that offer answers to each of these questions and more. Check it out!

What’s the Point?

Our mission is to provide clear, reliable information on all of the different voice to text solutions currently on the market, in order to help consumers in any of the following situations:

  • An individual interested in trying out a voice to text software for personal use
  • A business trying to find a voice to text solution for their transcription or dictation needs
  • An interested party trying to learn about how voice to text works and why it matters

Which category do you fall into?No matter what situation you’re in, we’ve got you covered at VoicetoText.me.Read on to find answers to any questions you might have about voice to.me solutions.

What’s the Best Voice to.me Solution?

The short answer? LilySpeech.While of course every person will have different voice to.me needs depending on their situation, based on our review here at VoicetoText.me, we find LilySpeech to be the best combination of quality and value.As we’ve written about elsewhere on VoicetoText.me, Google currently has the best voice to text engine – and it’s not close. LilySpeech is the first PC program to house Google’s superior service into a neat and tidy little program.And even though Google’s voice to text engine already boasts 99.5% accuracy, LilySpeech utilizes several additional features such as custom words and canned answers to improve accuracy to even higher levels. This degree of customizability is what sets LilySpeech apart.LilySpeech provides its superior service at a cost of $2.49 per month, which is hundreds of dollars cheaper than some weaker highbrow alternatives. The program is also available for 30 days free of charge, in order to give interested consumers a chance to try out voice to text for themselves.Regardless of your situation and of your voice to text needs, LilySpeech offers value for everyone. Currently, there is no better way to access the incredible voice to text capacity of Google’s technology, unless you want to do all your dictating on a smartphone.With a month free, there’s no risk for individuals interested in seeing what voice to text is all about. We recommend that consumers check out LilySpeech for more information and start their voice to text experience today.

Will Voice to Text Engines Ever Beat Out Humans?

According to Google, they will.In a recent research presentation at Google, the lead laboratory team responsible for Google speech recognition revealed an ambitious goal: to provide voice to text solutions that outcompete human transcription and human dictation, and to do so with no humans involved!In a humorous talk, Google’s researchers claimed that the most important thing to do when designing good.me is to get rid of all the humans.While the human intelligence over at Google is certainly necessary for their success, it’s no joke that the system they have set up is almost fully automated. As Google’s voice to text engine utilizes machine learning algorithms to perform pattern recognition and analyzes mountains of live user data every day to hone its language rules, there truly isn’t much need for human intervention.As is Google’s philosophy in many areas, the researchers rely on their core strength: smart data analysis on a massive scale.The researchers believe that with the ability to harness powerful learning algorithms, the sky is the limit for what Google’s voice to text engine can achieve in terms of accuracy. And the scary thing is that they’re right. Google has already achieved levels of up to 99.5% accuracy, and there’s no reason to think that they’ll move in any direction but upwards.Human dictation of course will always be the gold standard, and there’s reason to believe that machines can’t take that from us.But it simply depends on your frame of reference. If the goal is to transcribe one single (very important) conversation with absolute accuracy, then perhaps a human presence is necessary in order to ensure that mistakes are noticed and corrected, and that ambiguity is dealt with in a sensitive way.On the other hand, if the goal is to transcribe every audio file on the internet, as Google has professed, then scale matters a lot more.In light of such a massive project, there’s no doubt that finding ways to automate will be more important than anything else. As it stands, at 99.5% accuracy Google only makes 5 errors out of every 1000 words transcribed. When you consider the amount of words present in every audio file on the internet, and when you further consider how many man-hours such a project would take, that rate of error doesn’t seem so bad!In summary, Google is well on its way to accomplishing its goal: To remove all of the humans from the act of transcription. With their amazing voice to text engine, they just might pull it off.

When Did Google’s New Voice to Text.me Come Out?

Well.technically it’s not new.The race for voice to text engines is actually quite old, if you consider the decades of academic research that preceded current mainstream voice to text engines. The ability to transcribe speech using automatic computer programs is almost as old as computers itself, and has been one of the hot button issues for linguistic science for decades.However, the story of Google’s voice to text engine dates back only to the 2000s.In the first decade of the 21st century, Google sunk a lot of research capital into the process of human speech processing. They wanted to understand two key things: (1) How does the ear interpret sounds as speech? (2) How does the brain use rules to organize speech sounds into consistent patterns of language?While the research was highly technical, (and very prolific!), the end result was nothing short of revolutionary.Based on this incredible research into the human speech recognition apparatus, in 2008 Google patented a design for a new voice to text engine. At the time, Apple was in the process of unleashing Siri on the.me world, offering a digital, voice-controlled assistant to help users navigate and simplify the smartphone environment. Google had to find a way to keep up.In 2011, they did exactly that, fully incorporating a brand new voice to text engine into their smartphone apps.Subsequently, Google’s voice to text engine has gotten exponentially better, as its automated machine learning algorithms field millions upon millions of user queries. The sky is the limit with how accurate Google’s voice to text engine can get, and it’s already more accurate than all of its competitors!So while Google’s.me isn’t new, the ability for PC users to access it is. With the recent release of LilySpeech, interested consumers can check out Google’s revolutionary voice to text innovation free of charge for 30 days.Why wait!

How Do Voice to Text Engines Work?

We’re glad you asked! Here at VoicetoText.me, we find few things more interesting than the process of speech recognition, and how humans have coded machines to do it for us.Let’s follow the process of a voice to text engine step by step. We’ll use Google’s voice to text engine (as run by the LilySpeech program) to illustrate.

Step 1: Convert Sound Waves to Electrical Signals

I bet you never considered this step! Sound travels by causing air molecules to vibrate. These vibrations then cause a little tiny mechanical piece of a microphone to move. These movements, in turn, are transcribed kind of like the lie detector machines on TV into scribbly audio wave patterns. LilySpeech is responsible for coordinating your computer’s microphone and sending those signals over to Google.

Step 2: Convert Electrical Signals to Speech Sounds

While this step might seem unimportant, being able to recognize which sounds are for speech and which sounds aren’t is actually one of the most fascinatingly difficult parts of human speech recognition. Scientists call it the “cocktail party effect,” and Google had to do some serious work to make a speech to text engine that screened out background noise with a comparable degree of accuracy!

Step 3: Convert Speech Sounds to Words

Once the speech sounds have been isolated from audio wave files, then those speech sounds can be sent via the web to Google’s massive servers, where sophisticated pattern recognition algorithms match the audio waves to words. This is essentially an astronomically-sized system of trial and error, and after billions of user inputs Google’s machine learning algorithms have gotten exceedingly efficient at it!

Step 4: Convert Words to Sentences

Individual sounds – even when correctly identified – are a far cry from actual human language. Google’s voice to text engine uses pre-specified language rules to guess at what sentences the user is actually trying to compose. For example, homophones must be correctly identified according to context: you wouldn’t say “I knead to know,” or “I’m needing the dough!”

Step 5: Convert Sentences to Text

At this point Google’s servers have done most of the heavy lifting, and they send back their best guess through the internet to your local desktop LilySpeech program. LilySpeech, in turn, will then make some final corrections based on user-specified rules – such as correcting regular spelling errors. This helps take Google’s 99.5% accuracy and boost it even higher!And there you have it! With those 5 steps Google and LilySpeech combine together to take the words coming out of your mouth and convert them to text on the screen. All other voice to text engines work pretty similar to this, though none so efficiently.Consumers interested in checking out the process for themselves can try out LilySpeech free of charge for 30 days, and see the magic of voice to text for themselves.

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You Should Decide on Voice to text solutions?

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