Welcome to SpeechTyping.com
Speech to text, a dream for decades comes true. You can type by just speaking. The speech-to-text software works with a speech recognition system; which recognizes your voice and convert it into text. It's much faster than conventional keyboard typing.
Now, you just need to plug-in your microphone, start speaking and the speech-to-text converter app will convert your spoken words into text. Type by speak is 100% free for you. Just select your language from below and start speak to get text.
18. Bahasa Malay Speech to Text
19. 60 Languages Speech to Text
For Translation between Languages, Click on Easy Translator
Note 1 : This software works only in Google Chrome (Version 25 or higher) Browser. If you are using another browser, it will not work. Download and Install Google Chrome Here.
You can use this speech-to-text converter app, to type anything, anywhere, anytime. This app will help you in completing your day-to-days tasks and save lots of time and money. You can type articles, blogs, emails etc. by using speech to text service. Currently speech typing support all major languages like English, Spanish, French, German, Portuguese, Russian, Italian, Polish, Indonesian, Malay and More than 60 languages.
Let's Explore Speech Recognition
Speech to Text (STT) - is an assistive technology tool that can write words by speaking them aloud.
Automatic Speech Recognition (ASR) - is a technology that allows us to use our voices to speak with a computer interface in a way that like human conversation.
Speech-to-Text is also known as "dictation-to-text", "voice-to-text", "speech typing", "voice typing" or “speech recognition” technology.
When the microphone receives the speech, an analog to digital converter used to convert your spoken sound waves into digital counter part. First of all this digital data is filtered by the software and unwanted ambient noise is removed. This digital data is divided into small segments called "Phonemes". The users Phonemes are then matched with known phonemes. For example : there are roughly 40 phonemes in the English language. A statistical model is used to run the contextual phoneme and compared to a large library that is fitted inside of known words and sentences. Than the software identifies with respect to the context of the input and selects what fit them best and gives that as an output on the screen in the form of readable text.