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Speechify is a mobile, chrome extension and desktop app that reads text aloud using a computer-generated text to speech voice. [1] [2] [3]The app also uses optical character recognition technology to turn physical books or printed text into audio which can be played in your own voice or in that of a celebrity.
Festival Speech Synthesis System: CSTR? 2014, December MIT-like license: FreeTTS: Paul Lamere Philip Kwok Dirk Schnelle-Walka Willie Walker... 2001, December 14 2009, March 9 BSD: LumenVox: LumenVox: 2011 2019 Proprietary: Microsoft Speech API: Microsoft: 1995 2012 Bundled with Windows: VoiceText: ReadSpeaker (Formerly Neospeech) 2002 2017 ...
Apps such as textPlus and WhatsApp use Text-to-Speech to read notifications aloud and provide voice-reply functionality. Google Cloud Text-to-Speech is powered by WaveNet, [5] software created by Google's UK-based AI subsidiary DeepMind, which was bought by Google in 2014. [6] It tries to distinguish from its competitors, Amazon and Microsoft. [7]
Gnopernicus uses these in a number of places: to know when text should and should not be interrupted, to better concatenate speech, and to sequence speech in different voices. Benchmarks conducted by Sun in 2002 on Solaris showed that FreeTTS ran two to three times faster than Flite at the time.
The speech patterns of the SAPI 4 and SAPI 5 versions of the text-to-speech voices are different from each other. The SAPI 4 versions of Microsoft Sam, Microsoft Mike and Microsoft Mary can be used on Windows XP, Windows Vista , and later with a third-party program (like Speakonia and TTSReader) installed on the machine that supports these ...
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Dragon NaturallySpeaking uses a minimal user interface. As an example, dictated words appear in a floating tooltip as they are spoken (though there is an option to suppress this display to increase speed), and when the speaker pauses, the program transcribes the words into the active window at the location of the cursor.
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.
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