Transcribe (whisper) and translate (gpt) voice into LRC file.
Project description
Open-Lyrics
Open-Lyrics is a Python library that transcribes voice files using
faster-whisper, and translates/polishes the resulting text
into .lrc
files in the desired language using OpenAI-GPT.
This new project is rapidly underway, and we welcome any issues or pull requests.
Installation
-
Please install CUDA and cuDNN first according to https://opennmt.net/CTranslate2/installation.html to enable
faster-whisper
. -
Add your OpenAI API key to environment variable
OPENAI_API_KEY
. -
Install whisperx
pip install git+https://github.com/m-bain/whisperx.git
-
This project can be installed from PyPI:
pip install openlrc
or install directly from GitHub:
pip install git+https://github.com/zh-plus/Open-Lyrics
Usage
from openlrc import LRCer
lrcer = LRCer()
lrcer.run('./data/test.mp3', target_lang='zh-cn') # Generate translated ./data/test.lrc with default translate prompt.
Todo
- [Efficiency] Batched translate/polish for GPT request (enable contextual ability).
- [Efficiency] Concurrent support for GPT request.
- [Efficiency & Transcription Quality] Use whisperx for transcription.
- [Translation Quality] Make translate prompt more robust according to https://github.com/openai/openai-cookbook.
- [Usability] Automatically fix json encoder error using GPT.
- [Efficiency] Asynchronously perform transcription and translation for multiple audio inputs.
- [Usability] Multiple output format support.
- [Efficiency] Add Azure OpenAI Service support.
- [Usability] Add local LLM support.
- [Others] Add transcribed examples.
- Song
- Podcast
- Audiobook
Credits
Project details
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