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  2. 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.

  3. 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.

  4. Voice font - Wikipedia

    en.wikipedia.org/wiki/Voice_font

    A voice font is a computer-generated voice that can be controlled by specifying parameters such as speed and pitch and made to pronounce text input. The concept is akin to that of a text font or a MIDI instrument in the sense that the same input may easily be represented in several different ways based on the design of each font.

  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 31 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. Hitler’s AI translated speeches go viral on TikTok - AOL

    www.aol.com/hitler-ai-translated-speeches-viral...

    Misguided TikTokers are using AI to translate Adolf Hitler’s speeches into English – and racking up millions of clicks on the under-fire platform, according to a watchdog media report.

  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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