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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. Microsoft text-to-speech voices - Wikipedia

    en.wikipedia.org/.../Microsoft_text-to-speech_voices

    None of these voices match the Cortana text-to-speech voice which can be found on Windows Phone 8.1, Windows 10, and Windows 10 Mobile. In an attempt to unify its software with Windows 10 , all of Microsoft's current platforms use the same text-to-speech voices except for Microsoft David and a few others.

  5. CereProc - Wikipedia

    en.wikipedia.org/wiki/CereProc

    DSP often makes recorded speech sound less natural. CereProc's parametric voices produce speech synthesis based on statistical modelling methodologies. In this system, the frequency spectrum (vocal tract), fundamental frequency (vocal source), and duration of speech are modelled simultaneously. Speech waveforms are generated from these ...

  6. 15.ai - Wikipedia

    en.wikipedia.org/wiki/15.ai

    15.ai was a free to use artificial intelligence web application that generated text-to-speech voices from ... high-quality text-to-speech model has been a primary ...

  7. WaveNet - Wikipedia

    en.wikipedia.org/wiki/WaveNet

    WaveNet is a deep neural network for generating raw audio. It was created by researchers at London-based AI firm DeepMind.The technique, outlined in a paper in September 2016, [1] is able to generate relatively realistic-sounding human-like voices by directly modelling waveforms using a neural network method trained with recordings of real speech.

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