Speech Synthesis: FastPitch 1.1 Model Card
Model overview
FastPitch is a mel-spectrogram generator, designed to be used as the first part of a neural text-to-speech system in conjunction with a neural vocoder. This model uses the International Phonetic Alphabet (IPA) for inference and training.
Model architecture
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.
Training
Dataset
This model is trained on a mix of public and proprietary data sampled at 22050Hz, and can be used to generate a German voice. This model supports 1 male voice.
How to Use this Model
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.
The encryption key for this model is ZzZjce65zzGZ9o
Input
German text strings
Output
Mel spectrogram of shape (batch x mel_channels x time)
References
[1] FastPitch: Parallel Text-to-speech with Pitch Prediction
Suggested Reading
Refer to the Riva documentation for more information.
License
By downloading and using the models and resources packaged with Riva Conversational AI, you accept the terms of the Riva license.
Ethical AI
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