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](http://research.baidu.com) and other research groups.
In particular, it features the latest [WaveFlow] (https://arxiv.org/abs/1912.01219) model proposed by Baidu Research. WaveFlow is a small-footprint generative flow for raw audio, which is directly trained with maximum likelihood. It generates high-fidelity speech as WaveNet, while synthesizing serval orders of magnitude faster as it only requires a few sequential steps to generate very long waveforms. Furthermore, it can significantly reduce the likelihood gap that has existed between autoregressive models and flow-based models for efficient synthesis. Finally, our small-footprint WaveFlow has
only 5.9M parameters, which is 15 times smaller than WaveGlow. It can generate 22.05 kHz high-fidelity audio around 40 times faster than real-time on a V100 GPU without engineered inference kernels.