PaddleSpeech README

The project's README from github.com/PaddlePaddle/PaddleSpeech. As one markdown file: README.md.

(简体中文|English)

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

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

Community

Installation

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

Dependency Introduction

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

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PaddleSpeech (PaddlePaddle/PaddleSpeech)

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PaddleSpeech
What is this?PaddleSpeech is an open-source speech and audio toolkit built on the PaddlePaddle platform, covering tasks like Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Speaker Verification, Speech Translation, Keyword Spotting and Punctuation Restoration. It won the NAACL2022 Best Demo Award.
Is this a Python library, or something more?It's a Python library/toolkit you install via pip or source, but it also ships ready-to-use CLI commands and an optional Server (including a Streaming Server) so you don't have to write code to try the models.
How do I install and run it?Install PaddlePaddle first, then install PaddleSpeech either via pip or by compiling from source (recommended), after which you can call the models through the CLI or the Python API.
Do I need PaddlePaddle and a specific Python version first?Yes — you need gcc >= 4.8.5, Python >= 3.8, and PaddlePaddle itself installed before PaddleSpeech, picking the PaddlePaddle build that matches your CPU/GPU.
Any install pitfalls I should know about?Installation can get tricky with conda environments, librosa dependencies, gcc issues and Kaldi setup — there's a dedicated troubleshooting doc, and the Speech Translation demo specifically needs pre-compiled Kaldi tools that only work on Ubuntu.
Does it only run on Linux, or also Windows and Mac?Linux is the recommended OS, but Windows and Mac OSX are also supported.
What speech tasks does it actually support out of the box?ASR, TTS, Speaker Verification, Keyword Spotting, Audio/Sound Classification, Speech Translation and Punctuation Restoration, with streaming versions of ASR and TTS built for production use.
What makes its Chinese TTS special?It has a rule-based Chinese text frontend handling text normalization and grapheme-to-phoneme conversion, including polyphone and tone sandhi rules tailored to Chinese context.
Can I clone a voice or fine-tune TTS on a new speaker?Yes — there are voice cloning examples (e.g. AISHELL-3 with an ECAPA-TDNN speaker encoder), a TTS finetuning workflow, and ERNIE-SAT models for voice cloning and speech editing.
What underlying models and datasets does it build on?It integrates mainstream datasets like LibriSpeech, LJSpeech, AIShell and CSMSC with models such as Conformer, Wav2vec2, HuBERT, WavLM, Whisper and VITS.
What are similar projects?MOSS-TTS-Nano, Speech, TTS, faster-whisper, pyvideotrans, FireRedAudio, whisperX, sherpa-onnx
Which topics is it in?vocoder, voice-recognition, self-supervised-learning, speech, asr, toolkit, voice-cloning, speech-synthesis, audio-processing, whisper, speech-to-text, speech-recognition
Creator
PaddlePaddle
Size
71.2 MB
Stars
12.7K
Updated
CommitJun 12Releaser1.5.0Mar 05
Age
8y
Commits · 90 Days