from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readmes-readable.md
1.What is this repo or project? (You can reuse the repo description you used earlier because this section doesn’t have to be long.)
2.How does it work?
3.Who will use this repo or project?
4.What is the goal of this project?
-->
**PaddleSpeech** is an open-source toolkit on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform for a variety of critical tasks in speech, with state-of-art and influential models.
**PaddleSpeech** is an open-source toolkit on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform for a variety of critical tasks in speech, with the state-of-art and influential models.
For more synthesized audios, please refer to [PaddleSpeech Text-To-Speech samples](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html).
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 modules, and deployment process. To be more specific, this toolkit features at:
- **Fast and Light-weight**: we provide high-speed and ultra-lightweight models that are convenient for industrial deployment.
- **Rule-based Chinese frontend**: our frontend contains Text Normalization (TN) and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.
- **Rule-based Chinese frontend**: our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.
- **Varieties of Functions that Vitalize both Industrial and Academia**:
- *Implementation of critical audio tasks*: this toolkit contains audio functions like Speech Translation (ST), Automatic Speech Recognition (ASR), Text-To-Speech Synthesis (TTS), Voice Cloning(VC), Punctuation Restoration, etc.
- *Implementation of critical audio tasks*: this toolkit contains audio functions like Speech Translation, Automatic Speech Recognition, Text-To-Speech Synthesis, Voice Cloning, etc.
- *Integration of mainstream models and datasets*: the toolkit implements modules that participate in the whole pipeline of the speech tasks, and uses mainstream datasets like LibriSpeech, LJSpeech, AIShell, CSMSC, etc. See also [model lists](#models-list) for more details.
- *Cross-domain application*: as an extension of the application of traditional audio tasks, we combine the aforementioned tasks with other fields like NLP.
- *Cascaded models application*: as an extension of the application of traditional audio tasks, we combine the workflows of aforementioned tasks with other fields like Natural language processing (NLP), like Punctuation Restoration.
Let's install PaddleSpeech with only a few lines of code!
# Community
>Note: The official name is still deepspeech. 2021/10/26
You are warmly welcome to submit questions in [discussions](https://github.com/PaddlePaddle/DeepSpeech/discussions) and bug reports in [issues](https://github.com/PaddlePaddle/DeepSpeech/issues)! Also, we highly appreciate if you would like to contribute to this project!
If you are using Ubuntu, PaddleSpeech can be set up with pip installation (with root privilege).
If you are from China, we strongly recommend you join our PaddleSpeech WeChat group. Scan the following WeChat QR code and get in touch with the other developers in this community!
If you want to set up PaddleSpeech in other environment, please see the [ASR installation](docs/source/asr/install.md) and [TTS installation](docs/source/tts/install.md) documents for all the alternatives.
If you want to set up PaddleSpeech in other environment, please see the [installation](./docs/source/install.md) documents for all the alternatives.
## Quick Start
> Note: the current links to `English ASR` and `English TTS` are not valid.
Just a quick test of our functions: [English ASR](link/hubdetail?name=deepspeech2_aishell&en_category=AutomaticSpeechRecognition) and [English TTS](link/hubdetail?name=fastspeech2_baker&en_category=TextToSpeech) by typing message or upload your own audio file.
# Quick Start
Developers can have a try of our model with only a few lines of code.
A tiny **ASR** DeepSpeech2 model training on toy set of LibriSpeech:
A tiny DeepSpeech2**Speech-To-Text** model training on toy set of LibriSpeech:
If you want to try more functions like training and tuning, please see [ASR getting started](docs/source/asr/getting_started.md) and [TTS Basic Use](/docs/source/tts/basic_usage.md).
If you want to try more functions like training and tuning, please see [Speech-To-Text Quick Start](./docs/source/asr/quick_start.md) and [Text-To-Speech Quick Start](./docs/source/tts/quick_start.md).
## Models List
# Models List
PaddleSpeech supports a series of most popular models, summarized in [released models](./docs/source/released_model.md) with available pretrained models.
PaddleSpeech supports a series of most popular models, summarized in [released models](./docs/source/released_models.md) with available pretrained models.
ASR module contains *Acoustic Model* and *Language Model*, with the following details:
Speech-To-Text module contains *Acoustic Model* and *Language Model*, with the following details:
<!---
The current hyperlinks redirect to [Previous Parakeet](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples).
-->
> Note: The `Link` should be code path rather than download links.
<table>
<tablestyle="width:100%">
<thead>
<tr>
<th>ASR Module Type</th>
<th>Speech-To-Text Module Type</th>
<th>Dataset</th>
<th>Model Type</th>
<th>Link</th>
@ -141,76 +179,61 @@ The current hyperlinks redirect to [Previous Parakeet](https://github.com/Paddle
</thead>
<tbody>
<tr>
<tdrowspan="6">Acoustic Model</td>
<tdrowspan="4">Aishell</td>
<td>2 Conv + 5 LSTM layers with only forward direction</td>
<ahref ="https://deepspeech.bj.bcebos.com/zh_lm/zhidao_giga.klm">Mandarin Language Model Large</a>
<ahref ="./examples/timit/s1"> u2-timit</a>
</td>
</tr>
</tbody>
</table>
PaddleSpeech TTS mainly contains three modules: *Text Frontend*, *Acoustic Model* and *Vocoder*. Acoustic Model and Vocoder models are listed as follow:
PaddleSpeech Text-To-Speech mainly contains three modules: *Text Frontend*, *Acoustic Model* and *Vocoder*. Acoustic Model and Vocoder models are listed as follow:
@ -309,30 +306,44 @@ PaddleSpeech TTS mainly contains three modules: *Text Frontend*, *Acoustic Model
</tbody>
</table>
## Tutorials
Normally, [Speech SoTA](https://paperswithcode.com/area/speech) gives you an overview of the hot academic topics in speech. If you want to focus on the two tasks in PaddleSpeech, you will find the following guidelines are helpful to grasp the core ideas.
The original ASR module is based on [Baidu's DeepSpeech](https://arxiv.org/abs/1412.5567) which is an independent product named [DeepSpeech](https://deepspeech.readthedocs.io). However, the toolkit aligns almost all the SoTA modules in the pipeline. Specifically, these modules are
Normally, [Speech SoTA](https://paperswithcode.com/area/speech) gives you an overview of the hot academic topics in speech. To focus on the tasks in PaddleSpeech, you will find the following guidelines are helpful to grasp the core ideas.
- [Overview](./docs/source/introduction.md)
- Quick Start
- [Dependencies](./docs/source/dependencies.md) and [Installation](./docs/source/install.md)
- [Quick Start of Speech-To-Text](./docs/source/asr/quick_start.md)
- [Quick Start of Text-To-Speech](./docs/source/tts/quick_start.md)
- [Chinese Rule Based Text Frontend](./docs/source/tts/zh_text_frontend.md)
- [Test Audio Samples](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html) and [PaddleSpeech VS. Espnet](https://paddlespeech.readthedocs.io/en/latest/tts/demo_2.html)
The TTS module is originally called [Parakeet](https://github.com/PaddlePaddle/Parakeet), and now merged with DeepSpeech. If you are interested in academic research about this function, please see [TTS research overview](https://github.com/PaddlePaddle/DeepSpeech/tree/develop/docs/source/tts#overview). Also, [this document](https://paddleparakeet.readthedocs.io/en/latest/released_models.html) is a good guideline for the pipeline components.
## FAQ and Contributing
# FAQ and Contributing
You are warmly welcome to submit questions in [discussions](https://github.com/PaddlePaddle/DeepSpeech/discussions) and bug reports in [issues](https://github.com/PaddlePaddle/DeepSpeech/issues)! Also, we highly appreciate if you would like to contribute to this project!
## License
# License and Acknowledgement
PaddleSpeech is provided under the [Apache-2.0 License](./LICENSE).
## Acknowledgement
PaddleSpeech depends on a lot of open source repos. See [references](docs/source/reference.md) for more information.
PaddleSpeech depends on a lot of open source repositories. See [references](./docs/source/reference.md) for more information.
# Citation
To cite PaddleSpeech for research, please use the following format.
```tex
@misc{ppspeech2021,
title={PaddleSpeech, a toolkit for audio processing based on PaddlePaddle.},
TianYuan
3 years ago
committed by
GitHub
