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  2. 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.

  3. Retrieval-based Voice Conversion - Wikipedia

    en.wikipedia.org/wiki/Retrieval-Based_Voice...

    Retrieval-based Voice Conversion (RVC) is an open source voice conversion AI algorithm that enables realistic speech-to-speech transformations, accurately preserving the intonation and audio characteristics of the original speaker.

  4. Speech Recognition Grammar Specification - Wikipedia

    en.wikipedia.org/wiki/Speech_Recognition_Grammar...

    A grammar processor that does not support recursive grammars has the expressive power of a finite-state machine or regular expression language. If the speech recognizer returned just a string containing the actual words spoken by the user, the voice application would have to do the tedious job of extracting the semantic meaning from those words.

  5. Speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Speech_synthesis

    This is an accepted version of this page This is the latest accepted revision, reviewed on 1 January 2025. Artificial production of human speech Automatic announcement A synthetic voice announcing an arriving train in Sweden. Problems playing this file? See media help. Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech ...

  6. VALL-E - Wikipedia

    en.wikipedia.org/wiki/VALL-E

    VALL-E is a generative artificial intelligence system for speech synthesis developed by Microsoft Research and announced on January 5, 2023. [1] It can "recreate any voice from a three-second sample clip". [2] It has been trained on 60,000 hours of English language speech from Meta’s audio library LibriLight. [3]

  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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