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  2. Auto-Tune - Wikipedia

    en.wikipedia.org/wiki/Auto-Tune

    Auto-Tune can also be used as an effect to distort the human voice when pitch is raised or lowered significantly, [9] such that the voice is heard to leap from note to note stepwise, like a synthesizer. [10] Auto-Tune has become standard equipment in professional recording studios. [11]

  3. 15.ai - Wikipedia

    en.wikipedia.org/wiki/15.ai

    15.ai was a free non-commercial web application that used artificial intelligence to generate text-to-speech voices of fictional characters from popular media. [1] Created by an artificial intelligence researcher known as 15 during their time at the Massachusetts Institute of Technology, the application allowed users to make characters from video games, television shows, and movies speak ...

  4. HTML audio - Wikipedia

    en.wikipedia.org/wiki/HTML_audio

    The adoption of HTML audio, as with HTML video, has become polarized between proponents of free and patent-encumbered formats. In 2007, the recommendation to use Vorbis was retracted from the HTML5 specification by the W3C together with that to use Ogg Theora, citing the lack of a format accepted by all the major browser vendors.

  5. Pitch correction - Wikipedia

    en.wikipedia.org/wiki/Pitch_correction

    Pitch correction devices became popular in the late 1990s as a distinctively electronic, vocoder-like voice effect. A notable example of Auto-Tune-based pitch correction is the Cher effect, so named because producer Mark Taylor originated the effect in her 1998 hit song "Believe". [4]

  6. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    Audio deepfake technology, also referred to as voice cloning or deepfake audio, is an application of artificial intelligence designed to generate speech that convincingly mimics specific individuals, often synthesizing phrases or sentences they have never spoken.

  7. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    A stack of dilated casual convolutional layers used in WaveNet [1]. In September 2016, DeepMind proposed WaveNet, a deep generative model of raw audio waveforms, demonstrating that deep learning-based models are capable of modeling raw waveforms and generating speech from acoustic features like spectrograms or mel-spectrograms.