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Online Demo

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。

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

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

• Offical Demo: https://www.mulanai.com/product/tts/
• HuggingFace Demo: https://huggingface.co/spaces/shibing624/parrots

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

python examples/tts_gradio_demo.py

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'}

example: examples/demo_tts.py

import sys
sys.path.append('..')
import parrots
from parrots.tts import TextToSpeech
parrots_path = parrots.__path__[0]
sys.path.append(parrots_path)

m = TextToSpeech(
    speaker_model_path="shibing624/parrots-gpt-sovits-speaker-maimai",
    speaker_name="MaiMai",
)
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

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

• asr、tts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.wav是asr方法的audio_file_path参数，输入的音频文件（required）

• BELLE-2/Belle-distilwhisper-large-v2-zh

• shibing624/parrots-gpt-sovits-speaker

• shibing624/parrots-gpt-sovits-speaker-maimai

• Issue(建议)：
• 邮件我：xuming: [email protected]
• 微信我：加我微信号：xuming624, 进Python-NLP交流群，备注：姓名-公司名-NLP

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}},
}

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。

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：

• 在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。

• EAT: Enhanced ASR-TTS for Self-supervised Speech Recognition
• PaddlePaddle/PaddleSpeech
• NVIDIA/NeMo

• coqui-ai/TTS
• keonlee9420/Expressive-FastSpeech2
• TensorSpeech/TensorflowTTS
• RVC-Boss/GPT-SoVITS