**PaddleSpeech** is an open-source toolkit on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform for two critical tasks in Speech - Automatic Speech Recognition (ASR) and Text-To-Speech Synthesis (TTS), with modules involving state-of-art and influential models.
**PaddleSpeech** is an open-source toolkit on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform for two critical tasks in Speech - Automatic Speech Recognition (ASR) and Text-To-Speech Synthesis (TTS), with modules involving state-of-art and influential models.
Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing module, and deployment. Besides, this toolkit also features at:
- **Rule-based Chinese frontend**: we utilize plenty of Chinese datasets and corpora to enhance user experience, including CSMSC and Baidu Internal Corpus.
- **Supporting of ASR streaming and non-streaming data**: This toolkit contains non-streaming models like [Baidu's DeepSpeech2](http://proceedings.mlr.press/v48/amodei16.pdf), [Transformer](https://arxiv.org/abs/1706.03762) and [Conformer](https://arxiv.org/abs/2005.08100). And for streaming models, we have [Baidu's DeepSpeech2](http://proceedings.mlr.press/v48/amodei16.pdf) and [U2](https://arxiv.org/pdf/2012.05481.pdf).
- **Varieties of mainstream models**: The toolkit integrates modules that participate in the whole pipeline of both ASR and TTS, [See also model lists](#models-list).
> Notes: It is better to add a brief getting started.
## Table of Contents
The contents of this README is as follow:
- [Table of Contents](#table-of-contents)
- [Features](#features)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Models List](#models-list)
@ -43,42 +51,6 @@ how they can use it
- [License](#license)
- [Acknowledgement](#acknowledgement)
## Features
Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing module, and deployment.
> Note: 1.Better add hyperlinks for code path; 2.The current `Features` is a bit long. Is there any idea to shorten this section?
The features of **ASR** are summarized as follows:
- **Used datasets**
- Aishell, THCHS30, TIMIT and Librispeech
- **Model support of streaming and non-streaming data**
- Non-streaming: [Baidu's DeepSpeech2](http://proceedings.mlr.press/v48/amodei16.pdf), [Transformer](https://arxiv.org/abs/1706.03762) and [Conformer](https://arxiv.org/abs/2005.08100)
- Streaming: [Baidu's DeepSpeech2](http://proceedings.mlr.press/v48/amodei16.pdf) and [U2](https://arxiv.org/pdf/2012.05481.pdf)
- **Voice Cloning**: Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis, GE2E
## Installation
> Note: The installation guidance of TTS and ASR is now separated.
@ -92,16 +64,90 @@ Please see the [ASR installation](docs/source/asr/install.md) and [TTS installat
## Quick Start
> Note: It is better to use code blocks rather than hyperlinks.
Please see [ASR getting started](docs/source/asr/getting_started.md) ([tiny test](examples/tiny/s0/README.md)) and [TTS Basic Use](/docs/source/tts/basic_usage.md).
## Models List
PaddleSpeech ASR supports a lot of mainstream models. For more information, please refer to [ASRModels](./docs/source/asr/released_model.md).
PaddleSpeech ASR supports a lot of mainstream models, which are summarized as follow. For more information, please refer to [ASRModels](./docs/source/asr/released_model.md).
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The current hyperlinks redirect to [Previous Parakeet](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples).
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<table>
<thead>
<tr>
<th>ASR Module Type</th>
<th>Model Type</th>
<th>Dataset</th>
<th>Link</th>
</tr>
</thead>
<tbody>
<tr>
<tdrowspan="6">Acoustic Model</td>
<td>2 Conv + 5 LSTM layers with only forward direction </td>
PaddleSpeech TTS mainly contains three modules: *Text Frontend*, *Acoustic Model* and *Vocoder*. Acoustic Model and Vocoder models are listed as follow:
Mingxue-Xu
4 years ago
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