Parakeet aims to provide a flexible, efficient and state-of-the-art text-to-speech toolkit for the open-source community. It is built on PaddlePaddle Fluid dynamic graph and includes many influential TTS models proposed by Baidu Research and other research groups.
In particular, it features the latest WaveFlow model proposed by Baidu Research.
- WaveFlow can synthesize 22.05 kHz high-fidelity speech around 40x faster than real-time on a Nvidia V100 GPU without engineered inference kernels, which is faster than WaveGlow and serveral orders of magnitude faster than WaveNet.
- WaveFlow is a small-footprint flow-based model for raw audio. It has only 5.9M parameters, which is 15x smalller than WaveGlow (87.9M).
- WaveFlow is directly trained with maximum likelihood without probability density distillation and auxiliary losses as used in Parallel WaveNet and ClariNet, which simplifies the training pipeline and reduces the cost of development.
In order to facilitate exploiting the existing TTS models directly and developing the new ones, Parakeet selects typical models and provides their reference implementations in PaddlePaddle. Further more, Parakeet abstracts the TTS pipeline and standardizes the procedure of data preprocessing, common modules sharing, model configuration, and the process of training and synthesis. The models supported here include Vocoders and end-to-end TTS models:
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Vocoders
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TTS models
May-07-2021, Add an example for voice cloning in Chinese. Check examples/tacotron2_aishell3.
Make sure the library libsndfile1 is installed, e.g., on Ubuntu.
sudo apt-get install libsndfile1See install for more details. This repo requires PaddlePaddle 2.0.0rc1 or above.
pip install -U paddle-parakeetor
git clone https://github.com/PaddlePaddle/Parakeet
cd Parakeet
pip install -e .See install for more details.
Entries to the introduction, and the launch of training and synthsis for different example models:
Check our website for audio sampels.
Parakeet is provided under the Apache-2.0 license.