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Forward TTS model(s)

A general feed-forward TTS model implementation that can be configured to different architectures by setting different encoder and decoder networks. It can be trained with either pre-computed durations (from pre-trained Tacotron) or an alignment network that learns the text to audio alignment from the input data.

Currently we provide the following pre-configured architectures:

  • FastSpeech:

    It's a feed-forward model TTS model that uses Feed Forward Transformer (FFT) modules as the encoder and decoder.

  • FastPitch:

    It uses the same FastSpeech architecture that is conditioned on fundemental frequency (f0) contours with the promise of more expressive speech.

  • SpeedySpeech:

    It uses Residual Convolution layers instead of Transformers that leads to a more compute friendly model.

  • FastSpeech2 (TODO):

    Similar to FastPitch but it also uses a spectral energy values as an addition.

Important resources & papers

ForwardTTSArgs

.. autoclass:: TTS.tts.models.forward_tts.ForwardTTSArgs
    :members:

ForwardTTS Model

.. autoclass:: TTS.tts.models.forward_tts.ForwardTTS
    :members:

FastPitchConfig

.. autoclass:: TTS.tts.configs.fast_pitch_config.FastPitchConfig
    :members:

SpeedySpeechConfig

.. autoclass:: TTS.tts.configs.speedy_speech_config.SpeedySpeechConfig
    :members:

FastSpeechConfig

.. autoclass:: TTS.tts.configs.fast_speech_config.FastSpeechConfig
    :members: