([简体中文](./README_cn.md)|English)
< p align = "center" >
< img src = "./docs/images/PaddleSpeech_logo.png" / >
< / p >
< p align = "center" >
< a href = "./LICENSE" > < img src = "https://img.shields.io/badge/license-Apache%202-red.svg" > < / a >
< a href = "https://github.com/PaddlePaddle/PaddleSpeech/releases" > < img src = "https://img.shields.io/github/v/release/PaddlePaddle/PaddleSpeech?color=ffa" > < / a >
< a href = "support os" > < img src = "https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg" > < / a >
< a href = "" > < img src = "https://img.shields.io/badge/python-3.7+-aff.svg" > < / a >
< a href = "https://github.com/PaddlePaddle/PaddleSpeech/graphs/contributors" > < img src = "https://img.shields.io/github/contributors/PaddlePaddle/PaddleSpeech?color=9ea" > < / a >
< a href = "https://github.com/PaddlePaddle/PaddleSpeech/commits" > < img src = "https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleSpeech?color=3af" > < / a >
< a href = "https://github.com/PaddlePaddle/PaddleSpeech/issues" > < img src = "https://img.shields.io/github/issues/PaddlePaddle/PaddleSpeech?color=9cc" > < / a >
< a href = "https://github.com/PaddlePaddle/PaddleSpeech/stargazers" > < img src = "https://img.shields.io/github/stars/PaddlePaddle/PaddleSpeech?color=ccf" > < / a >
< a href = "=https://pypi.org/project/paddlespeech/" > < img src = "https://img.shields.io/pypi/dm/PaddleSpeech" > < / a >
< a href = "=https://pypi.org/project/paddlespeech/" > < img src = "https://static.pepy.tech/badge/paddlespeech" > < / a >
< a href = "https://huggingface.co/spaces" > < img src = "https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue" > < / a >
< / p >
< div align = "center" >
< h4 >
< a href = "#quick-start" > Quick Start < / a >
| < a href = "#documents" > Documents < / a >
| < a href = "#model-list" > Models List < / a >
| < a href = "https://aistudio.baidu.com/aistudio/course/introduce/25130" > AIStudio Courses < / a >
| < a href = "https://arxiv.org/abs/2205.12007" > NAACL2022 Best Demo Award Paper < / a >
| < a href = "https://gitee.com/paddlepaddle/PaddleSpeech" > Gitee < / a >
< / h4 >
< / div >
------------------------------------------------------------------------------------
**PaddleSpeech** is an open-source toolkit on [PaddlePaddle ](https://github.com/PaddlePaddle/Paddle ) platform for a variety of critical tasks in speech and audio, with the state-of-art and influential models.
**PaddleSpeech** won the [NAACL2022 Best Demo Award ](https://2022.naacl.org/blog/best-demo-award/ ), please check out our paper on [Arxiv ](https://arxiv.org/abs/2205.12007 ).
##### Speech Recognition
< div align = "center" >
< table style = "width:100%" >
< thead >
< tr >
< th > Input Audio < / th >
< th width = "550" > Recognition Result < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200 style=" max-width: 100 % ; " > < / a > < br >
< / td >
< td > I knocked at the door on the ancient side of the building.< / td >
< / tr >
< tr >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200" style = "max-width: 100%;" > < / a > < br >
< / td >
< td > 我认为跑步最重要的就是给我带来了身体健康。< / td >
< / tr >
< / tbody >
< / table >
< / div >
##### Speech Translation (English to Chinese)
< div align = "center" >
< table style = "width:100%" >
< thead >
< tr >
< th > Input Audio < / th >
< th width = "550" > Translations Result < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200 style=" max-width: 100 % ; " > < / a > < br >
< / td >
< td > 我 在 这栋 建筑 的 古老 门上 敲门。< / td >
< / tr >
< / tbody >
< / table >
< / div >
##### Text-to-Speech
< div align = "center" >
< table style = "width:100%" >
< thead >
< tr >
< th width = "550" > Input Text< / th >
< th > Synthetic Audio< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Life was like a box of chocolates, you never know what you're gonna get.< / td >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/tacotron2_ljspeech_waveflow_samples_0.2/sentence_1.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200" style = "max-width: 100%;" > < / a > < br >
< / td >
< / tr >
< tr >
< td > 早上好, 今天是2020/10/29, 最低温度是-3°C。< / td >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200" style = "max-width: 100%;" > < / a > < br >
< / td >
< / tr >
< tr >
< td > 季姬寂,集鸡,鸡即棘鸡。棘鸡饥叽,季姬及箕稷济鸡。鸡既济,跻姬笈,季姬忌,急咭鸡,鸡急,继圾几,季姬急,即籍箕击鸡,箕疾击几伎,伎即齑,鸡叽集几基,季姬急极屐击鸡,鸡既殛,季姬激,即记《季姬击鸡记》。< / td >
< td align = "center" >
< a href = "https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/jijiji.wav" rel = "nofollow" >
< img align = "center" src = "./docs/images/audio_icon.png" width = "200" style = "max-width: 100%;" > < / a > < br >
< / td >
< / tr >
< / tbody >
< / table >
< / div >
For more synthesized audios, please refer to [PaddleSpeech Text-to-Speech samples ](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html ).
##### Punctuation Restoration
< div align = "center" >
< table style = "width:100%" >
< thead >
< tr >
< th width = "390" > Input Text < / th >
< th width = "390" > Output Text < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > 今天的天气真不错啊你下午有空吗我想约你一起去吃饭< / td >
< td > 今天的天气真不错啊!你下午有空吗?我想约你一起去吃饭。< / td >
< / tr >
< / tbody >
< / table >
< / div >
### 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 modules, and deployment process. To be more specific, this toolkit features at:
- 📦 **Ease of Use** : low barriers to install, [CLI ](#quick-start ), [Server ](#quick-start-server ), and [Streaming Server ](#quick-start-streaming-server ) is available to quick-start your journey.
- 🏆 **Align to the State-of-the-Art** : we provide high-speed and ultra-lightweight models, and also cutting-edge technology.
- 🏆 **Streaming ASR and TTS System** : we provide production ready streaming asr and streaming tts system.
- 💯 **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 Automatic Speech Recognition, Text-to-Speech Synthesis, Speaker Verfication, KeyWord Spotting, Audio Classification, and Speech Translation, 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 list ](#model-list ) for more details.
- 🧩 *Cascaded models application* : as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV).
### Recent Update
- 👑 2022.11.01: Add [Adversarial Loss ](https://arxiv.org/pdf/1907.04448.pdf ) for [Chinese English mixed TTS ](./examples/zh_en_tts/tts3 ).
- 🔥 2022.10.26: Add [Prosody Prediction ](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/other/rhy ) for TTS.
- 🎉 2022.10.21: Add [SSML ](https://github.com/PaddlePaddle/PaddleSpeech/discussions/2538 ) for TTS Chinese Text Frontend.
- 👑 2022.10.11: Add [Wav2vec2ASR ](./examples/librispeech/asr3 ), wav2vec2.0 fine-tuning for ASR on LibriSpeech.
- 🔥 2022.09.26: Add Voice Cloning, TTS finetune, and [ERNIE-SAT ](https://arxiv.org/abs/2211.03545 ) in [PaddleSpeech Web Demo ](./demos/speech_web ).
- ⚡ 2022.09.09: Add AISHELL-3 Voice Cloning [example ](./examples/aishell3/vc2 ) with ECAPA-TDNN speaker encoder.
- ⚡ 2022.08.25: Release TTS [finetune ](./examples/other/tts_finetune/tts3 ) example.
- 🔥 2022.08.22: Add [ERNIE-SAT ](https://arxiv.org/abs/2211.03545 ) models: [ERNIE-SAT-vctk ](./examples/vctk/ernie_sat )、[ERNIE-SAT-aishell3](./examples/aishell3/ernie_sat)、[ERNIE-SAT-zh_en](./examples/aishell3_vctk/ernie_sat).
- 🔥 2022.08.15: Add [g2pW ](https://github.com/GitYCC/g2pW ) into TTS Chinese Text Frontend.
- 🔥 2022.08.09: Release [Chinese English mixed TTS ](./examples/zh_en_tts/tts3 ).
- ⚡ 2022.08.03: Add ONNXRuntime infer for TTS CLI.
- 🎉 2022.07.18: Release VITS: [VITS-csmsc ](./examples/csmsc/vits )、[VITS-aishell3](./examples/aishell3/vits)、[VITS-VC](./examples/aishell3/vits-vc).
- 🎉 2022.06.22: All TTS models support ONNX format.
- 🍀 2022.06.17: Add [PaddleSpeech Web Demo ](./demos/speech_web ).
- 👑 2022.05.13: Release [PP-ASR ](./docs/source/asr/PPASR.md )、[PP-TTS](./docs/source/tts/PPTTS.md)、[PP-VPR](docs/source/vpr/PPVPR.md).
- 👏🏻 2022.05.06: `PaddleSpeech Streaming Server` is available for `Streaming ASR` with `Punctuation Restoration` and `Token Timestamp` and `Text-to-Speech` .
- 👏🏻 2022.05.06: `PaddleSpeech Server` is available for `Audio Classification` , `Automatic Speech Recognition` and `Text-to-Speech` , `Speaker Verification` and `Punctuation Restoration` .
- 👏🏻 2022.03.28: `PaddleSpeech CLI` is available for `Speaker Verification` .
- 🤗 2021.12.14: [ASR ](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR ) and [TTS ](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS ) Demos on Hugging Face Spaces are available!
- 👏🏻 2021.12.10: `PaddleSpeech CLI` is available for `Audio Classification` , `Automatic Speech Recognition` , `Speech Translation (English to Chinese)` and `Text-to-Speech` .
### Community
- Scan the QR code below with your Wechat, you can access to official technical exchange group and get the bonus ( more than 20GB learning materials, such as papers, codes and videos ) and the live link of the lessons. Look forward to your participation.
< div align = "center" >
< img src = "https://user-images.githubusercontent.com/30135920/196351517-19dece6b-d6ea-448e-a341-d6bfe5712ec1.jpg" width = "200" / >
< / div >
## Installation
We strongly recommend our users to install PaddleSpeech in **Linux** with *python>=3.7* and *paddlepaddle>=2.4rc* .
### **Dependency Introduction**
+ gcc >= 4.8.5
+ paddlepaddle >= 2.4rc
+ python >= 3.7
+ OS support: Linux(recommend), Windows, Mac OSX
PaddleSpeech depends on paddlepaddle. For installation, please refer to the official website of [paddlepaddle ](https://www.paddlepaddle.org.cn/en ) and choose according to your own machine. Here is an example of the cpu version.
```bash
pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
```
You can also specify the version of paddlepaddle or install the develop version.
```bash
# install 2.3.1 version. Note, 2.3.1 is just an example, please follow the minimum dependency of paddlepaddle for your selection
pip install paddlepaddle==2.3.1 -i https://mirror.baidu.com/pypi/simple
# install develop version
pip install paddlepaddle==0.0.0 -f https://www.paddlepaddle.org.cn/whl/linux/cpu-mkl/develop.html
```
There are two quick installation methods for PaddleSpeech, one is pip installation, and the other is source code compilation (recommended).
### pip install
```shell
pip install pytest-runner
pip install paddlespeech
```
### source code compilation
```shell
git clone https://github.com/PaddlePaddle/PaddleSpeech.git
cd PaddleSpeech
pip install pytest-runner
pip install .
```
For more installation problems, such as conda environment, librosa-dependent, gcc problems, kaldi installation, etc., you can refer to this [installation document ](./docs/source/install.md ). If you encounter problems during installation, you can leave a message on [#2150 ](https://github.com/PaddlePaddle/PaddleSpeech/issues/2150 ) and find related problems
< a name = "quickstart" > < / a >
## Quick Start
Developers can have a try of our models with [PaddleSpeech Command Line ](./paddlespeech/cli/README.md ) or Python. Change `--input` to test your own audio/text and support 16k wav format audio.
**You can also quickly experience it in AI Studio 👉🏻 [PaddleSpeech API Demo ](https://aistudio.baidu.com/aistudio/projectdetail/4353348?sUid=2470186&shared=1&ts=1660876445786 )**
Test audio sample download
```shell
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
```
### Automatic Speech Recognition
< details > < summary >   ( Click to expand) Open Source Speech Recognition< / summary >
**command line experience**
```shell
paddlespeech asr --lang zh --input zh.wav
```
**Python API experience**
```python
>>> from paddlespeech.cli.asr.infer import ASRExecutor
>>> asr = ASRExecutor()
>>> result = asr(audio_file="zh.wav")
>>> print(result)
我认为跑步最重要的就是给我带来了身体健康
```
< / details >
### Text-to-Speech
< details > < summary >   Open Source Speech Synthesis< / summary >
Output 24k sample rate wav format audio
**command line experience**
```shell
paddlespeech tts --input "你好,欢迎使用百度飞桨深度学习框架!" --output output.wav
```
**Python API experience**
```python
>>> from paddlespeech.cli.tts.infer import TTSExecutor
>>> tts = TTSExecutor()
>>> tts(text="今天天气十分不错。", output="output.wav")
```
- You can experience in [Huggingface Spaces ](https://huggingface.co/spaces ) [TTS Demo ](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS )
< / details >
### Audio Classification
< details > < summary >   An open-domain sound classification tool< / summary >
Sound classification model based on 527 categories of AudioSet dataset
**command line experience**
```shell
paddlespeech cls --input zh.wav
```
**Python API experience**
```python
>>> from paddlespeech.cli.cls.infer import CLSExecutor
>>> cls = CLSExecutor()
>>> result = cls(audio_file="zh.wav")
>>> print(result)
Speech 0.9027186632156372
```
< / details >
### Voiceprint Extraction
< details > < summary >   Industrial-grade voiceprint extraction tool< / summary >
**command line experience**
```shell
paddlespeech vector --task spk --input zh.wav
```
**Python API experience**
```python
>>> from paddlespeech.cli.vector import VectorExecutor
>>> vec = VectorExecutor()
>>> result = vec(audio_file="zh.wav")
>>> print(result) # 187维向量
[ -0.19083306 9.474295 -14.122263 -2.0916545 0.04848729
4.9295826 1.4780062 0.3733844 10.695862 3.2697146
-4.48199 -0.6617882 -9.170393 -11.1568775 -1.2358263 ...]
```
< / details >
### Punctuation Restoration
< details > < summary >   Quick recovery of text punctuation, works with ASR models< / summary >
**command line experience**
```shell
paddlespeech text --task punc --input 今天的天气真不错啊你下午有空吗我想约你一起去吃饭
```
**Python API experience**
```python
>>> from paddlespeech.cli.text.infer import TextExecutor
>>> text_punc = TextExecutor()
>>> result = text_punc(text="今天的天气真不错啊你下午有空吗我想约你一起去吃饭")
今天的天气真不错啊!你下午有空吗?我想约你一起去吃饭。
```
< / details >
### Speech Translation
< details > < summary >   End-to-end English to Chinese Speech Translation Tool< / summary >
Use pre-compiled kaldi related tools, only support experience in Ubuntu system
**command line experience**
```shell
paddlespeech st --input en.wav
```
**Python API experience**
```python
>>> from paddlespeech.cli.st.infer import STExecutor
>>> st = STExecutor()
>>> result = st(audio_file="en.wav")
['我 在 这栋 建筑 的 古老 门上 敲门 。']
```
< / details >
< a name = "quickstartserver" > < / a >
## Quick Start Server
Developers can have a try of our speech server with [PaddleSpeech Server Command Line ](./paddlespeech/server/README.md ).
**You can try it quickly in AI Studio (recommend): [SpeechServer ](https://aistudio.baidu.com/aistudio/projectdetail/4354592?sUid=2470186&shared=1&ts=1660877827034 )**
**Start server**
```shell
paddlespeech_server start --config_file ./demos/speech_server/conf/application.yaml
```
**Access Speech Recognition Services**
```shell
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```
**Access Text to Speech Services**
```shell
paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav
```
**Access Audio Classification Services**
```shell
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
```
For more information about server command lines, please see: [speech server demos ](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_server )
< a name = "quickstartstreamingserver" > < / a >
## Quick Start Streaming Server
Developers can have a try of [streaming asr ](./demos/streaming_asr_server/README.md ) and [streaming tts ](./demos/streaming_tts_server/README.md ) server.
**Start Streaming Speech Recognition Server**
```
paddlespeech_server start --config_file ./demos/streaming_asr_server/conf/application.yaml
```
**Access Streaming Speech Recognition Services**
```
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```
**Start Streaming Text to Speech Server**
```
paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
```
**Access Streaming Text to Speech Services**
```
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav
```
For more information please see: [streaming asr ](./demos/streaming_asr_server/README.md ) and [streaming tts ](./demos/streaming_tts_server/README.md )
< a name = "ModelList" > < / a >
## Model List
PaddleSpeech supports a series of most popular models. They are summarized in [released models ](./docs/source/released_model.md ) and attached with available pretrained models.
< a name = "SpeechToText" > < / a >
**Speech-to-Text** contains *Acoustic Model* , *Language Model* , and *Speech Translation* , with the following details:
< table style = "width:100%" >
< thead >
< tr >
< th > Speech-to-Text Module Type< / th >
< th > Dataset< / th >
< th > Model Type< / th >
< th > Example< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td rowspan = "4" > Speech Recogination< / td >
< td rowspan = "2" > Aishell< / td >
< td > DeepSpeech2 RNN + Conv based Models< / td >
< td >
< a href = "./examples/aishell/asr0" > deepspeech2-aishell< / a >
< / td >
< / tr >
< tr >
< td > Transformer based Attention Models < / td >
< td >
< a href = "./examples/aishell/asr1" > u2.transformer.conformer-aishell< / a >
< / td >
< / tr >
< tr >
< td > Librispeech< / td >
< td > Transformer based Attention Models < / td >
< td >
< a href = "./examples/librispeech/asr0" > deepspeech2-librispeech< / a > / < a href = "./examples/librispeech/asr1" > transformer.conformer.u2-librispeech< / a > / < a href = "./examples/librispeech/asr2" > transformer.conformer.u2-kaldi-librispeech< / a >
< / td >
< / td >
< / tr >
< tr >
< td > TIMIT< / td >
< td > Unified Streaming & Non-streaming Two-pass< / td >
< td >
< a href = "./examples/timit/asr1" > u2-timit< / a >
< / td >
< / tr >
< tr >
< td > Alignment< / td >
< td > THCHS30< / td >
< td > MFA< / td >
< td >
< a href = ".examples/thchs30/align0" > mfa-thchs30< / a >
< / td >
< / tr >
< tr >
< td rowspan = "1" > Language Model< / td >
< td colspan = "2" > Ngram Language Model< / td >
< td >
< a href = "./examples/other/ngram_lm" > kenlm< / a >
< / td >
< / tr >
< tr >
< td rowspan = "2" > Speech Translation (English to Chinese)< / td >
< td rowspan = "2" > TED En-Zh< / td >
< td > Transformer + ASR MTL< / td >
< td >
< a href = "./examples/ted_en_zh/st0" > transformer-ted< / a >
< / td >
< / tr >
< tr >
< td > FAT + Transformer + ASR MTL< / td >
< td >
< a href = "./examples/ted_en_zh/st1" > fat-st-ted< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "TextToSpeech" > < / a >
**Text-to-Speech** in PaddleSpeech mainly contains three modules: *Text Frontend* , *Acoustic Model* and *Vocoder* . Acoustic Model and Vocoder models are listed as follow:
< table >
< thead >
< tr >
< th > Text-to-Speech Module Type < / th >
< th > Model Type < / th >
< th > Dataset < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Text Frontend < / td >
< td colspan = "2" >   < / td >
< td >
< a href = "./examples/other/tn" > tn< / a > / < a href = "./examples/other/g2p" > g2p< / a >
< / td >
< / tr >
< tr >
< td rowspan = "5" > Acoustic Model< / td >
< td > Tacotron2< / td >
< td > LJSpeech / CSMSC< / td >
< td >
< a href = "./examples/ljspeech/tts0" > tacotron2-ljspeech< / a > / < a href = "./examples/csmsc/tts0" > tacotron2-csmsc< / a >
< / td >
< / tr >
< tr >
< td > Transformer TTS< / td >
< td > LJSpeech< / td >
< td >
< a href = "./examples/ljspeech/tts1" > transformer-ljspeech< / a >
< / td >
< / tr >
< tr >
< td > SpeedySpeech< / td >
< td > CSMSC< / td >
< td >
< a href = "./examples/csmsc/tts2" > speedyspeech-csmsc< / a >
< / td >
< / tr >
< tr >
< td > FastSpeech2< / td >
< td > LJSpeech / VCTK / CSMSC / AISHELL-3 / ZH_EN / finetune< / td >
< td >
< a href = "./examples/ljspeech/tts3" > fastspeech2-ljspeech< / a > / < a href = "./examples/vctk/tts3" > fastspeech2-vctk< / a > / < a href = "./examples/csmsc/tts3" > fastspeech2-csmsc< / a > / < a href = "./examples/aishell3/tts3" > fastspeech2-aishell3< / a > / < a href = "./examples/zh_en_tts/tts3" > fastspeech2-zh_en< / a > / < a href = "./examples/other/tts_finetune/tts3" > fastspeech2-finetune< / a >
< / td >
< / tr >
< tr >
< td > < a href = "https://arxiv.org/abs/2211.03545" > ERNIE-SAT< / a > < / td >
< td > VCTK / AISHELL-3 / ZH_EN< / td >
< td >
< a href = "./examples/vctk/ernie_sat" > ERNIE-SAT-vctk< / a > / < a href = "./examples/aishell3/ernie_sat" > ERNIE-SAT-aishell3< / a > / < a href = "./examples/aishell3_vctk/ernie_sat" > ERNIE-SAT-zh_en< / a >
< / td >
< / tr >
< tr >
< td rowspan = "6" > Vocoder< / td >
< td > WaveFlow< / td >
< td > LJSpeech< / td >
< td >
< a href = "./examples/ljspeech/voc0" > waveflow-ljspeech< / a >
< / td >
< / tr >
< tr >
< td > Parallel WaveGAN< / td >
< td > LJSpeech / VCTK / CSMSC / AISHELL-3< / td >
< td >
< a href = "./examples/ljspeech/voc1" > PWGAN-ljspeech< / a > / < a href = "./examples/vctk/voc1" > PWGAN-vctk< / a > / < a href = "./examples/csmsc/voc1" > PWGAN-csmsc< / a > / < a href = "./examples/aishell3/voc1" > PWGAN-aishell3< / a >
< / td >
< / tr >
< tr >
< td > Multi Band MelGAN< / td >
< td > CSMSC< / td >
< td >
< a href = "./examples/csmsc/voc3" > Multi Band MelGAN-csmsc< / a >
< / td >
< / tr >
< tr >
< td > Style MelGAN< / td >
< td > CSMSC< / td >
< td >
< a href = "./examples/csmsc/voc4" > Style MelGAN-csmsc< / a >
< / td >
< / tr >
< tr >
< td > HiFiGAN< / td >
< td > LJSpeech / VCTK / CSMSC / AISHELL-3< / td >
< td >
< a href = "./examples/ljspeech/voc5" > HiFiGAN-ljspeech< / a > / < a href = "./examples/vctk/voc5" > HiFiGAN-vctk< / a > / < a href = "./examples/csmsc/voc5" > HiFiGAN-csmsc< / a > / < a href = "./examples/aishell3/voc5" > HiFiGAN-aishell3< / a >
< / td >
< / tr >
< tr >
< td > WaveRNN< / td >
< td > CSMSC< / td >
< td >
< a href = "./examples/csmsc/voc6" > WaveRNN-csmsc< / a >
< / td >
< / tr >
< tr >
< td rowspan = "5" > Voice Cloning< / td >
< td > GE2E< / td >
< td > Librispeech, etc.< / td >
< td >
< a href = "./examples/other/ge2e" > GE2E< / a >
< / td >
< / tr >
< tr >
< td > SV2TTS (GE2E + Tacotron2)< / td >
< td > AISHELL-3< / td >
< td >
< a href = "./examples/aishell3/vc0" > VC0< / a >
< / td >
< / tr >
< tr >
< td > SV2TTS (GE2E + FastSpeech2)< / td >
< td > AISHELL-3< / td >
< td >
< a href = "./examples/aishell3/vc1" > VC1< / a >
< / td >
< / tr >
< tr >
< td > SV2TTS (ECAPA-TDNN + FastSpeech2)< / td >
< td > AISHELL-3< / td >
< td >
< a href = "./examples/aishell3/vc2" > VC2< / a >
< / td >
< / tr >
< tr >
< td > GE2E + VITS< / td >
< td > AISHELL-3< / td >
< td >
< a href = "./examples/aishell3/vits-vc" > VITS-VC< / a >
< / td >
< / tr >
< tr >
< td rowspan = "3" > End-to-End< / td >
< td > VITS< / td >
< td > CSMSC / AISHELL-3< / td >
< td >
< a href = "./examples/csmsc/vits" > VITS-csmsc< / a > / < a href = "./examples/aishell3/vits" > VITS-aishell3< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "AudioClassification" > < / a >
**Audio Classification**
< table style = "width:100%" >
< thead >
< tr >
< th > Task < / th >
< th > Dataset < / th >
< th > Model Type < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Audio Classification< / td >
< td > ESC-50< / td >
< td > PANN< / td >
< td >
< a href = "./examples/esc50/cls0" > pann-esc50< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "KeywordSpotting" > < / a >
**Keyword Spotting**
< table style = "width:100%" >
< thead >
< tr >
< th > Task < / th >
< th > Dataset < / th >
< th > Model Type < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Keyword Spotting< / td >
< td > hey-snips< / td >
< td > MDTC< / td >
< td >
< a href = "./examples/hey_snips/kws0" > mdtc-hey-snips< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "SpeakerVerification" > < / a >
**Speaker Verification**
< table style = "width:100%" >
< thead >
< tr >
< th > Task < / th >
< th > Dataset < / th >
< th > Model Type < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Speaker Verification< / td >
< td > VoxCeleb1/2< / td >
< td > ECAPA-TDNN< / td >
< td >
< a href = "./examples/voxceleb/sv0" > ecapa-tdnn-voxceleb12< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "SpeakerDiarization" > < / a >
**Speaker Diarization**
< table style = "width:100%" >
< thead >
< tr >
< th > Task < / th >
< th > Dataset < / th >
< th > Model Type < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Speaker Diarization< / td >
< td > AMI< / td >
< td > ECAPA-TDNN + AHC / SC< / td >
< td >
< a href = "./examples/ami/sd0" > ecapa-tdnn-ami< / a >
< / td >
< / tr >
< / tbody >
< / table >
< a name = "PunctuationRestoration" > < / a >
**Punctuation Restoration**
< table style = "width:100%" >
< thead >
< tr >
< th > Task < / th >
< th > Dataset < / th >
< th > Model Type < / th >
< th > Example < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Punctuation Restoration< / td >
< td > IWLST2012_zh< / td >
< td > Ernie Linear< / td >
< td >
< a href = "./examples/iwslt2012/punc0" > iwslt2012-punc0< / a >
< / td >
< / tr >
< / tbody >
< / table >
## Documents
Normally, [Speech SoTA ](https://paperswithcode.com/area/speech ), [Audio SoTA ](https://paperswithcode.com/area/audio ) and [Music SoTA ](https://paperswithcode.com/area/music ) give you an overview of the hot academic topics in the related area. To focus on the tasks in PaddleSpeech, you will find the following guidelines are helpful to grasp the core ideas.
- [Installation ](./docs/source/install.md )
- [Quick Start ](#quickstart )
- [Some Demos ](./demos/README.md )
- Tutorials
- [Automatic Speech Recognition ](./docs/source/asr/quick_start.md )
- [Introduction ](./docs/source/asr/models_introduction.md )
- [Data Preparation ](./docs/source/asr/data_preparation.md )
- [Ngram LM ](./docs/source/asr/ngram_lm.md )
- [Text-to-Speech ](./docs/source/tts/quick_start.md )
- [Introduction ](./docs/source/tts/models_introduction.md )
- [Advanced Usage ](./docs/source/tts/advanced_usage.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 )
- Speaker Verification
- [Audio Searching ](./demos/audio_searching/README.md )
- [Speaker Verification ](./demos/speaker_verification/README.md )
- [Audio Classification ](./demos/audio_tagging/README.md )
- [Speech Translation ](./demos/speech_translation/README.md )
- [Speech Server ](./demos/speech_server/README.md )
- [Released Models ](./docs/source/released_model.md )
- [Speech-to-Text ](#SpeechToText )
- [Text-to-Speech ](#TextToSpeech )
- [Audio Classification ](#AudioClassification )
- [Speaker Verification ](#SpeakerVerification )
- [Speaker Diarization ](#SpeakerDiarization )
- [Punctuation Restoration ](#PunctuationRestoration )
- [Community ](#Community )
- [Welcome to contribute ](#contribution )
- [License ](#License )
The Text-to-Speech module is originally called [Parakeet ](https://github.com/PaddlePaddle/Parakeet ), and now merged with this repository. If you are interested in academic research about this task, please see [TTS research overview ](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/docs/source/tts#overview ). Also, [this document ](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/tts/models_introduction.md ) is a good guideline for the pipeline components.
## ⭐ Examples
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): Use PaddleSpeech TTS to generate virtual human voice.**
< div align = "center" > < a href = "https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web" > < img src = "https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width = "500px" > < / a > < / div >
- [PaddleSpeech Demo Video ](https://paddlespeech.readthedocs.io/en/latest/demo_video.html )
- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): Use PaddleSpeech TTS and ASR to clone voice from videos.**
< div align = "center" >
< img src = "https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" / >
< / div >
## Citation
E2E/Streaming Transformer/Conformer ASR (#578)
* add cmvn and label smoothing loss layer
* add layer for transformer
* add glu and conformer conv
* add torch compatiable hack, mask funcs
* not hack size since it exists
* add test; attention
* add attention, common utils, hack paddle
* add audio utils
* conformer batch padding mask bug fix #223
* fix typo, python infer fix rnn mem opt name error and batchnorm1d, will be available at 2.0.2
* fix ci
* fix ci
* add encoder
* refactor egs
* add decoder
* refactor ctc, add ctc align, refactor ckpt, add warmup lr scheduler, cmvn utils
* refactor docs
* add fix
* fix readme
* fix bugs, refactor collator, add pad_sequence, fix ckpt bugs
* fix docstring
* refactor data feed order
* add u2 model
* refactor cmvn, test
* add utils
* add u2 config
* fix bugs
* fix bugs
* fix autograd maybe has problem when using inplace operation
* refactor data, build vocab; add format data
* fix text featurizer
* refactor build vocab
* add fbank, refactor feature of speech
* refactor audio feat
* refactor data preprare
* refactor data
* model init from config
* add u2 bins
* flake8
* can train
* fix bugs, add coverage, add scripts
* test can run
* fix data
* speed perturb with sox
* add spec aug
* fix for train
* fix train logitc
* fix logger
* log valid loss, time dataset process
* using np for speed perturb, remove some debug log of grad clip
* fix logger
* fix build vocab
* fix logger name
* using module logger as default
* fix
* fix install
* reorder imports
* fix board logger
* fix logger
* kaldi fbank and mfcc
* fix cmvn and print prarams
* fix add_eos_sos and cmvn
* fix cmvn compute
* fix logger and cmvn
* fix subsampling, label smoothing loss, remove useless
* add notebook test
* fix log
* fix tb logger
* multi gpu valid
* fix log
* fix log
* fix config
* fix compute cmvn, need paddle 2.1
* add cmvn notebook
* fix layer tools
* fix compute cmvn
* add rtf
* fix decoding
* fix layer tools
* fix log, add avg script
* more avg and test info
* fix dataset pickle problem; using 2.1 paddle; num_workers can > 0; ckpt save in exp dir;fix setup.sh;
* add vimrc
* refactor tiny script, add transformer and stream conf
* spm demo; librisppech scripts and confs
* fix log
* add librispeech scripts
* refactor data pipe; fix conf; fix u2 default params
* fix bugs
* refactor aishell scripts
* fix test
* fix cmvn
* fix s0 scripts
* fix ds2 scripts and bugs
* fix dev & test dataset filter
* fix dataset filter
* filter dev
* fix ckpt path
* filter test, since librispeech will cause OOM, but all test wer will be worse, since mismatch train with test
* add comment
* add syllable doc
* fix ds2 configs
* add doc
* add pypinyin tools
* fix decoder using blank_id=0
* mmseg with pybind11
* format code
3 years ago
To cite PaddleSpeech for research, please use the following format.
```text
@InProceedings {pmlr-v162-bai22d,
title = {{A}$^3${T}: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing},
author = {Bai, He and Zheng, Renjie and Chen, Junkun and Ma, Mingbo and Li, Xintong and Huang, Liang},
booktitle = {Proceedings of the 39th International Conference on Machine Learning},
pages = {1399--1411},
year = {2022},
volume = {162},
series = {Proceedings of Machine Learning Research},
month = {17--23 Jul},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v162/bai22d/bai22d.pdf},
url = {https://proceedings.mlr.press/v162/bai22d.html},
}
@inproceedings {zhang2022paddlespeech,
title = {PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit},
author = {Hui Zhang, Tian Yuan, Junkun Chen, Xintong Li, Renjie Zheng, Yuxin Huang, Xiaojie Chen, Enlei Gong, Zeyu Chen, Xiaoguang Hu, dianhai yu, Yanjun Ma, Liang Huang},
booktitle = {Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations},
year = {2022},
publisher = {Association for Computational Linguistics},
}
@inproceedings {zheng2021fused,
title={Fused acoustic and text encoding for multimodal bilingual pretraining and speech translation},
author={Zheng, Renjie and Chen, Junkun and Ma, Mingbo and Huang, Liang},
booktitle={International Conference on Machine Learning},
pages={12736--12746},
year={2021},
organization={PMLR}
}
```
< a name = "contribution" > < / a >
## Contribute to PaddleSpeech
You are warmly welcome to submit questions in [discussions ](https://github.com/PaddlePaddle/PaddleSpeech/discussions ) and bug reports in [issues ](https://github.com/PaddlePaddle/PaddleSpeech/issues )! Also, we highly appreciate if you are willing to contribute to this project!
### Contributors
< p align = "center" >
< a href = "https://github.com/zh794390558" > < img src = "https://avatars.githubusercontent.com/u/3038472?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Jackwaterveg" > < img src = "https://avatars.githubusercontent.com/u/87408988?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/yt605155624" > < img src = "https://avatars.githubusercontent.com/u/24568452?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Honei" > < img src = "https://avatars.githubusercontent.com/u/11361692?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/KPatr1ck" > < img src = "https://avatars.githubusercontent.com/u/22954146?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/kuke" > < img src = "https://avatars.githubusercontent.com/u/3064195?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/lym0302" > < img src = "https://avatars.githubusercontent.com/u/34430015?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/SmileGoat" > < img src = "https://avatars.githubusercontent.com/u/56786796?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/xinghai-sun" > < img src = "https://avatars.githubusercontent.com/u/7038341?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/pkuyym" > < img src = "https://avatars.githubusercontent.com/u/5782283?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/LittleChenCc" > < img src = "https://avatars.githubusercontent.com/u/10339970?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/qingen" > < img src = "https://avatars.githubusercontent.com/u/3139179?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/D-DanielYang" > < img src = "https://avatars.githubusercontent.com/u/23690325?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Mingxue-Xu" > < img src = "https://avatars.githubusercontent.com/u/92848346?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/745165806" > < img src = "https://avatars.githubusercontent.com/u/20623194?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/jerryuhoo" > < img src = "https://avatars.githubusercontent.com/u/24245709?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/WilliamZhang06" > < img src = "https://avatars.githubusercontent.com/u/97937340?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/chrisxu2016" > < img src = "https://avatars.githubusercontent.com/u/18379485?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/iftaken" > < img src = "https://avatars.githubusercontent.com/u/30135920?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/lfchener" > < img src = "https://avatars.githubusercontent.com/u/6771821?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/BarryKCL" > < img src = "https://avatars.githubusercontent.com/u/48039828?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/mmglove" > < img src = "https://avatars.githubusercontent.com/u/38800877?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/gongel" > < img src = "https://avatars.githubusercontent.com/u/24390500?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/luotao1" > < img src = "https://avatars.githubusercontent.com/u/6836917?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/wanghaoshuang" > < img src = "https://avatars.githubusercontent.com/u/7534971?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/kslz" > < img src = "https://avatars.githubusercontent.com/u/54951765?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/JiehangXie" > < img src = "https://avatars.githubusercontent.com/u/51190264?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/david-95" > < img src = "https://avatars.githubusercontent.com/u/15189190?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/THUzyt21" > < img src = "https://avatars.githubusercontent.com/u/91456992?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/buchongyu2" > < img src = "https://avatars.githubusercontent.com/u/29157444?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/iclementine" > < img src = "https://avatars.githubusercontent.com/u/16222986?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/phecda-xu" > < img src = "https://avatars.githubusercontent.com/u/46859427?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/freeliuzc" > < img src = "https://avatars.githubusercontent.com/u/23568094?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/ZeyuChen" > < img src = "https://avatars.githubusercontent.com/u/1371212?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/ccrrong" > < img src = "https://avatars.githubusercontent.com/u/101700995?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/AK391" > < img src = "https://avatars.githubusercontent.com/u/81195143?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/qingqing01" > < img src = "https://avatars.githubusercontent.com/u/7845005?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/0x45f" > < img src = "https://avatars.githubusercontent.com/u/23097963?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/vpegasus" > < img src = "https://avatars.githubusercontent.com/u/22723154?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/ericxk" > < img src = "https://avatars.githubusercontent.com/u/4719594?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Betterman-qs" > < img src = "https://avatars.githubusercontent.com/u/61459181?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/sneaxiy" > < img src = "https://avatars.githubusercontent.com/u/32832641?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Doubledongli" > < img src = "https://avatars.githubusercontent.com/u/20540661?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/apps/dependabot" > < img src = "https://avatars.githubusercontent.com/in/29110?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/kvinwang" > < img src = "https://avatars.githubusercontent.com/u/6442159?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/chenkui164" > < img src = "https://avatars.githubusercontent.com/u/34813030?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/PaddleZhang" > < img src = "https://avatars.githubusercontent.com/u/97284124?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/billishyahao" > < img src = "https://avatars.githubusercontent.com/u/96406262?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/BrightXiaoHan" > < img src = "https://avatars.githubusercontent.com/u/25839309?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/jiqiren11" > < img src = "https://avatars.githubusercontent.com/u/82639260?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/ryanrussell" > < img src = "https://avatars.githubusercontent.com/u/523300?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/GT-ZhangAcer" > < img src = "https://avatars.githubusercontent.com/u/46156734?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/tensor-tang" > < img src = "https://avatars.githubusercontent.com/u/21351065?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/hysunflower" > < img src = "https://avatars.githubusercontent.com/u/52739577?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/oyjxer" > < img src = "https://avatars.githubusercontent.com/u/16233945?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/JamesLim-sy" > < img src = "https://avatars.githubusercontent.com/u/61349199?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/limpidezza" > < img src = "https://avatars.githubusercontent.com/u/71760778?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/windstamp" > < img src = "https://avatars.githubusercontent.com/u/34057289?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/AshishKarel" > < img src = "https://avatars.githubusercontent.com/u/58069375?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/chesterkuo" > < img src = "https://avatars.githubusercontent.com/u/6285069?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/YDX-2147483647" > < img src = "https://avatars.githubusercontent.com/u/73375426?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/AdamBear" > < img src = "https://avatars.githubusercontent.com/u/2288870?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/wwhu" > < img src = "https://avatars.githubusercontent.com/u/6081200?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/lispc" > < img src = "https://avatars.githubusercontent.com/u/2833376?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/harisankarh" > < img src = "https://avatars.githubusercontent.com/u/1307053?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/pengzhendong" > < img src = "https://avatars.githubusercontent.com/u/10704539?s=60&v=4" width = 75 height = 75 > < / a >
< a href = "https://github.com/Jackiexiao" > < img src = "https://avatars.githubusercontent.com/u/18050469?s=60&v=4" width = 75 height = 75 > < / a >
< / p >
## Acknowledgement
- Many thanks to [HighCWu ](https://github.com/HighCWu ) for adding [VITS-aishell3 ](./examples/aishell3/vits ) and [VITS-VC ](./examples/aishell3/vits-vc ) examples.
- Many thanks to [david-95 ](https://github.com/david-95 ) for fixing multi-punctuation bug、contributing to multiple program and data, and adding [SSML ](https://github.com/PaddlePaddle/PaddleSpeech/discussions/2538 ) for TTS Chinese Text Frontend.
- Many thanks to [BarryKCL ](https://github.com/BarryKCL ) for improving TTS Chinses Frontend based on [G2PW ](https://github.com/GitYCC/g2pW ).
- Many thanks to [yeyupiaoling ](https://github.com/yeyupiaoling )/[PPASR](https://github.com/yeyupiaoling/PPASR)/[PaddlePaddle-DeepSpeech](https://github.com/yeyupiaoling/PaddlePaddle-DeepSpeech)/[VoiceprintRecognition-PaddlePaddle](https://github.com/yeyupiaoling/VoiceprintRecognition-PaddlePaddle)/[AudioClassification-PaddlePaddle](https://github.com/yeyupiaoling/AudioClassification-PaddlePaddle) for years of attention, constructive advice and great help.
- Many thanks to [mymagicpower ](https://github.com/mymagicpower ) for the Java implementation of ASR upon [short ](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_sdk ) and [long ](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_long_audio_sdk ) audio files.
- Many thanks to [JiehangXie ](https://github.com/JiehangXie )/[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo) for developing Virtual Uploader(VUP)/Virtual YouTuber(VTuber) with PaddleSpeech TTS function.
- Many thanks to [745165806 ](https://github.com/745165806 )/[PaddleSpeechTask](https://github.com/745165806/PaddleSpeechTask) for contributing Punctuation Restoration model.
- Many thanks to [kslz ](https://github.com/745165806 ) for supplementary Chinese documents.
- Many thanks to [awmmmm ](https://github.com/awmmmm ) for contributing fastspeech2 aishell3 conformer pretrained model.
- Many thanks to [phecda-xu ](https://github.com/phecda-xu )/[PaddleDubbing](https://github.com/phecda-xu/PaddleDubbing) for developing a dubbing tool with GUI based on PaddleSpeech TTS model.
- Many thanks to [jerryuhoo ](https://github.com/jerryuhoo )/[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk) for developing a GUI tool based on PaddleSpeech TTS and code for making datasets from videos based on PaddleSpeech ASR.
- Many thanks to [vpegasus ](https://github.com/vpegasus )/[xuesebot](https://github.com/vpegasus/xuesebot) for developing a rasa chatbot,which is able to speak and listen thanks to PaddleSpeech.
- Many thanks to [chenkui164 ](https://github.com/chenkui164 )/[FastASR](https://github.com/chenkui164/FastASR) for the C++ inference implementation of PaddleSpeech ASR.
Besides, PaddleSpeech depends on a lot of open source repositories. See [references ](./docs/source/reference.md ) for more information.
< a name = "License" > < / a >
## License
PaddleSpeech is provided under the [Apache-2.0 License ](./LICENSE ).