PaddlePaddle/PaddleSpeech

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Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

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README

(简体中文|English)

Quick Start | Documents | Models List | AIStudio Courses | NAACL2022 Best Demo Award Paper | Gitee

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PaddleSpeech is an open-source toolkit on PaddlePaddle 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, please check out our paper on Arxiv.

Speech Recognition
Input Audio Recognition Result

I knocked at the door on the ancient side of the building.

我认为跑步最重要的就是给我带来了身体健康。

Speech Translation (English to Chinese)
Input Audio Translations Result

我 在 这栋 建筑 的 古老 门上 敲门。

Text-to-Speech
Input Text Synthetic Audio
Life was like a box of chocolates, you never know what you're gonna get.
早上好，今天是2020/10/29，最低温度是-3°C。
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》。
大家好，我是 parrot 虚拟老师，我们来读一首诗，我与春风皆过客，I and the spring breeze are passing by，你携秋水揽星河，you take the autumn water to take the galaxy。
宜家唔系事必要你讲，但系你所讲嘅说话将会变成呈堂证供。
各个国家有各个国家嘅国歌

For more synthesized audios, please refer to PaddleSpeech Text-to-Speech samples.

Punctuation Restoration
Input Text Output 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。

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:

Recent Update

of paddlepaddle.

Community

Installation

We strongly recommend our users to install PaddleSpeech in Linux with python>=3.8.

Dependency Introduction

+ gcc >= 4.8.5 + paddlepaddle + python >= 3.8 + OS support: Linux(recommend), Windows, Mac OSX

PaddleSpeech depends on paddlepaddle. For installation, please refer to the official website of paddlepaddle and choose according to your own machine. Here is an example of the cpu version.

pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
You can also specify the version of paddlepaddle or install the develop version. 
# install 2.4.1 version. Note, 2.4.1 is just an example, please follow the minimum dependency of paddlepaddle for your selection
pip install paddlepaddle==2.4.1 -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

pip install pytest-runner
pip install paddlespeech

source code compilation

git clone https://github.com/PaddlePaddle/PaddleSpeech.git
cd PaddleSpeech
pip install pytest-runner
pip install .

If you need to install in editable mode, you need to use --use-pep517. The command is as follows:


pip install -e . --use-pep517

For more installation problems, such as conda environment, librosa-dependent, gcc problems, kaldi installation, etc., you can refer to this installation document. If you encounter problems during installation, you can leave a message on #2150 and find related problems

Quick Start

Developers can have a try of our models with PaddleSpeech Command Line 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

Test audio sample download

wget -c https://paddlespeech.cdn.bcebos.com/PaddleAudio/zh.wav
wget -c https://paddlespeech.cdn.bcebos.com/PaddleAudio/en.wav

Automatic Speech Recognition

 （Click to expand）Open Source Speech Recognition

command line experience

paddlespeech asr --lang zh --input zh.wav

Python API experience

>>> 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

Text-to-Speech

 Open Source Speech Synthesis

Output 24k sample rate wav format audio

command line experience

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

>>> from paddlespeech.cli.tts.infer import TTSExecutor

>> tts = TTSExecutor()


>> tts(text="今天天气十分不错。", output="output.wav")

Audio Classification

 An open-domain sound classification tool

Sound classification model based on 527 categories of AudioSet dataset

command line experience

paddlespeech cls --input zh.wav

Python API experience

>>> from paddlespeech.cli.cls.infer import CLSExecutor

>> cls = CLSExecutor()


>> result = cls(audio_file="zh.wav")


>> print(result)

Speech 0.9027186632156372

Voiceprint Extraction

 Industrial-grade voiceprint extraction tool

command line experience

paddlespeech vector --task spk --input zh.wav

Python API experience

>>> 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 ...]

Punctuation Restoration

 Quick recovery of text punctuation, works with ASR models

command line experience

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

>>> 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。

Speech Translation

 End-to-end English to Chinese Speech Translation Tool

Use pre-compiled kaldi related tools, only support experience in Ubuntu system

command line experience

paddlespeech st --input en.wav

Python API experience

>>> 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 。']

Quick Start Server

Developers can have a try of our speech server with PaddleSpeech Server Command Line.

You can try it quickly in AI Studio (recommend): SpeechServer

Start server

paddlespeech_server start --config_file ./demos/speech_server/conf/application.yaml

Access Speech Recognition Services

paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav

Access Text to Speech Services

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 

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

Quick Start Streaming Server

Developers can have a try of streaming asr and streaming tts 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 and streaming tts

Model List

PaddleSpeech supports a series of most popular models. They are summarized in released models and attached with available pretrained models.

Speech-to-Text contains Acoustic Model, Language Model, and Speech Translation, with the following details:

Speech-to-Text Module Type Dataset Model Type Example
Speech Recogination Aishell DeepSpeech2 RNN + Conv based Models deepspeech2-aishell
Transformer based Attention Models u2.transformer.conformer-aishell
Librispeech Transformer based Attention Models deepspeech2-librispeech / transformer.conformer.u2-librispeech / transformer.conformer.u2-kaldi-librispeech
TIMIT Unified Streaming & Non-streaming Two-pass u2-timit
Alignment THCHS30 MFA mfa-thchs30
Language Model Ngram Language Model kenlm
Speech Translation (English to Chinese) TED En-Zh Transformer + ASR MTL transformer-ted
FAT + Transformer + ASR MTL fat-st-ted

Text-to-Speech in PaddleSpeech mainly contains three modules: Text Frontend, Acoustic Model and Vocoder. Acoustic Model and Vocoder models are listed as follow:

More Audio Trending projects

Git Homed · data from GitHub Trending and GitHub topic pages · updated daily · about sitemap · robots
Text-to-Speech Module Type Model Type Dataset