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eSpeak is a free and open-source, cross-platform, compact, software speech synthesizer.It uses a formant synthesis method, providing many languages in a relatively small file size. eSpeakNG (Next Generation) is a continuation of the original developer's project with more feedback from native speakers.
In 2010, Microsoft released the newer Speech Platform compatible voices for Speech Recognition and Text-to-Speech for use with client and server applications. These voices are available in 26 languages [3] and can be installed on Windows client and server operating systems. Speech Platform voices, unlike SAPI 5 voices, are female-only; no male ...
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.
Automatik Text Reader was a free and open source add-on for Firefox providing text-to-speech functions available from the Mozilla Add-ons collection. It supports multiple languages and accents and is capable of autonomously recognizing the language of written text and activating the respective speech synthesis engine. [1]
The Best Women’s Erotica of the Year, Volume 4, edited by Rachel Kramer Bussel Couples , by John Updike Aqua Erotica: 18 Erotic Stories for a Steamy Bath , by Mary Anne Mohanraj
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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