Skip to main content

Parrots, Automatic Speech Recognition(**ASR**), Text-To-Speech(**TTS**) toolkit

Project description

🇨🇳中文 | 🌐English | 📖文档/Docs | 🤖模型/Models


Parrots: ASR and TTS toolkit

PyPI version Downloads Contributions welcome GitHub contributors License Apache 2.0 python_vesion GitHub issues Wechat Group

Introduction

Parrots, Automatic Speech Recognition(ASR), Text-To-Speech(TTS) toolkit, support Chinese, English, Japanese, etc.

parrots实现了语音识别和语音合成模型一键调用,开箱即用,支持中英文。

Features

  1. ASR:基于distilwhisper实现的中文语音识别(ASR)模型,支持中、英等多种语言
  2. TTS:基于GPT-SoVITS训练的语音合成(TTS)模型,支持中、英、日等多种语言

Install

pip install torch # or conda install pytorch
pip install -r requirements.txt
pip install parrots

or

pip install torch # or conda install pytorch
git clone https://github.com/shibing624/parrots.git
cd parrots
python setup.py install

Demo

run example: examples/tts_gradio_demo.py to see the demo:

python examples/tts_gradio_demo.py

Usage

ASR(Speech Recognition)

example: examples/demo_asr.py

import os
import sys

sys.path.append('..')
from parrots import SpeechRecognition

pwd_path = os.path.abspath(os.path.dirname(__file__))

if __name__ == '__main__':
    m = SpeechRecognition()
    r = m.recognize_speech_from_file(os.path.join(pwd_path, 'tushuguan.wav'))
    print('[提示] 语音识别结果:', r)

output:

{'text': '北京图书馆'}

TTS(Speech Synthesis)

example: examples/demo_tts.py

import sys

sys.path.append('..')
from parrots import TextToSpeech
m = TextToSpeech(
    speaker_model_path="shibing624/parrots-gpt-sovits-speaker-maimai",
    speaker_name="MaiMai",
    device="cpu",
    half=False
)
m.predict(
    text="你好,欢迎来北京。welcome to the city.",
    text_language="auto",
    output_path="output_audio.wav"
)

output:

Save audio to output_audio.wav

命令行模式(CLI)

支持通过命令行方式执行ARS和TTS任务,代码:cli.py

> parrots -h                                    

NAME
    parrots

SYNOPSIS
    parrots COMMAND

COMMANDS
    COMMAND is one of the following:

     asr
       Entry point of asr, recognize speech from file

     tts
       Entry point of tts, generate speech audio from text

run:

pip install parrots -U
# asr example
parrots asr -h
parrots asr examples/tushuguan.wav

# tts example
parrots tts -h
parrots tts "你好,欢迎来北京。welcome to the city." output_audio.wav
  • asrtts是二级命令,asr是语音识别,tts是语音合成,默认使用的模型是中文模型
  • 各二级命令使用方法见parrots asr -h
  • 上面示例中examples/tushuguan.wavasr方法的audio_file_path参数,输入的音频文件(required)

Contact

  • Issue(建议):GitHub issues
  • 邮件我:xuming: xuming624@qq.com
  • 微信我:加我微信号:xuming624, 进Python-NLP交流群,备注:姓名-公司名-NLP

Citation

如果你在研究中使用了parrots,请按如下格式引用:

@misc{parrots,
  title={parrots: ASR and TTS Tool},
  author={Ming Xu},
  year={2024},
  howpublished={\url{https://github.com/shibing624/parrots}},
}

License

授权协议为 The Apache License 2.0,可免费用做商业用途。请在产品说明中附加parrots的链接和授权协议。

Contribute

项目代码还很粗糙,如果大家对代码有所改进,欢迎提交回本项目,在提交之前,注意以下两点:

  • tests添加相应的单元测试
  • 使用python -m pytest来运行所有单元测试,确保所有单测都是通过的

之后即可提交PR。

Reference

ASR(Speech Recognition)

TTS(Speech Synthesis)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

parrots-1.0.3.tar.gz (5.3 MB view details)

Uploaded Source

File details

Details for the file parrots-1.0.3.tar.gz.

File metadata

  • Download URL: parrots-1.0.3.tar.gz
  • Upload date:
  • Size: 5.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for parrots-1.0.3.tar.gz
Algorithm Hash digest
SHA256 fbdf113506027800e99b35412c2591031bfd4de445362c384c235a6603d1bcc8
MD5 78a610885e9b5db06a038502297e23ec
BLAKE2b-256 9bbaaa4da0c4682ff1ced733d5ce90ea77f1583b9f271f6859026d8ccc3d382b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page