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 fundamental 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¶
FastPitch: https://arxiv.org/abs/2006.06873
SpeedySpeech: https://arxiv.org/abs/2008.03802
FastSpeech: https://arxiv.org/pdf/1905.09263
FastSpeech2: https://arxiv.org/abs/2006.04558
Aligner Network: https://arxiv.org/abs/2108.10447
What is Pitch: https://www.britannica.com/topic/pitch-speech