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  2. List of sound chips - Wikipedia

    en.wikipedia.org/wiki/List_of_sound_chips

    Noise generator Sunsoft: Sunsoft 5B: 1992 3 Famicom cartridge Gimmick! Derivative of Yamaha YM2149F [28] Texas Instruments: SN76477: 1978 1 Space Invaders arcade system board, ABC 80 [29] LPC Speech Chips: 1978 1 Speak & Spell, Speak & Math, Speak & Read, arcade games

  3. DECtalk - Wikipedia

    en.wikipedia.org/wiki/DECtalk

    DECtalk. DECtalk[ 4] was a speech synthesizer and text-to-speech technology developed by Digital Equipment Corporation in 1983, [ 1] based largely on the work of Dennis Klatt at MIT, whose source-filter algorithm was variously known as KlattTalk or MITalk. [ 5][ 6] Uses ranged from interacting with the public to allowing those with speech ...

  4. Microsoft text-to-speech voices - Wikipedia

    en.wikipedia.org/wiki/Microsoft_text-to-speech...

    A speech sample of Microsoft Sam. The first part uses a variation of "The quick brown fox jumps over the lazy dog" panagram, while the second part showcases the "soi" glitch associated with Sam. Microsoft Sam is the default text-to-speech male voice in Microsoft Windows 2000 and Windows XP.

  5. 15.ai - Wikipedia

    en.wikipedia.org/wiki/15.ai

    15.ai is a non-commercial freeware artificial intelligence web application that generates natural emotive high-fidelity [a] text-to-speech voices from an assortment of fictional characters from a variety of media sources.

  6. Dr. Sbaitso - Wikipedia

    en.wikipedia.org/wiki/Dr._Sbaitso

    Dr. Sbaitso / ˈsbeɪtsoʊ / SBAY-tsoh / səˈb -/ / ˈzb -/ is an artificial intelligence speech synthesis program released late in 1991 [ 1] by Creative Labs in Singapore for MS-DOS -based personal computers. The name is an acronym for " S ound B laster A cting I ntelligent T ext-to- S peech O perator."

  7. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    e. 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 (vocoder). Deep neural networks (DNN) are trained using a large amount of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.

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