FastPitch is a fully-parallel text-to-speech model based on FastSpeech, conditioned on fundamental frequency contours. The model predicts pitch contours during inference. By altering these predictions, the generated speech can be more expressive, better match the semantic of the utterance, and in the end more engaging to the listener. FastPitch is based on a fully-parallel Transformer architecture, with much higher real-time factor than Tacotron2 for mel-spectrogram synthesis of a typical utterance.
FastPitch is intended to be used as the first part of a two stage speech synthesis pipeline. FastPitch takes text and produces a mel spectrogram. The second stage takes the generated mel spectrogram and returns audio.
Input: English text strings
Output: Mel spectrogram of shape (batch x mel_channels x time)
The provided .riva checkpoint can be used, in conjunction with a HifiGAN checkpoint, to generate speech with Riva. To deploy a TTS service with Riva, please refer to the Riva documentation.
This model is trained on LJSpeech sampled at 22050Hz, and can be used to generate female English voices with an American accent.
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FastPitch 2 paper: https://arxiv.org/abs/2006.06873