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  2. SitePal - Wikipedia

    en.wikipedia.org/wiki/SitePal

    Sitepal avatars talk through text-to-speech (tts) software. [2] A short paragraph can be written (up to 900 characters) and the text-to-speech engine will compile the actual speech, which can be reproduced and edited. The tts engine is not perfect, but it comes close to actual speech and is easy to understand.

  3. Neuro-sama - Wikipedia

    en.wikipedia.org/wiki/Neuro-sama

    [3] [4] Her responses are generated by a large language model, which are converted into a high-pitched, childlike voice using a text-to-speech application. According to Vedal, a separate AI model controls her in-game actions when she plays video games. [5] In a 2023 interview with Bloomberg News, he said that Neuro-sama was his full-time job. [6]

  4. Speechify - Wikipedia

    en.wikipedia.org/wiki/Speechify

    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.

  5. eSpeak - Wikipedia

    en.wikipedia.org/wiki/ESpeak

    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.

  6. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    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.

  7. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    It is necessary to collect clean and well-structured raw audio with the transcripted text of the original speech audio sentence. Second, the Text-To-Speech model must be trained using these data to build a synthetic audio generation model. Specifically, the transcribed text with the target speaker's voice is the input of the generation model ...

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