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The produced metadata file is intended to use in training/finetune of text to speech (TTS) models, and may use one of the following formats: \n- `file_id|transcribed_text`, or \n- `file_id|transcribed_text|speaker`, if a speaker label is provided. \n\nThis is similar to LJ Speech format, but lacks an additional field with normalized transcribed text for pronuciation. Particularly, `file_id|transcribed_text` may be used in projects like [piper-train](https://github.com/veralvx/piper-train), and `file_id|transcribed_text|speaker` in [xtts-finetune](https://github.com/veralvx/xtts-finetune).\n\n## Requirements\n\n- Python \u003e=3.10, \u003c3.14\n- [`uv`](https://docs.astral.sh/uv/)\n- `ffmpeg` (install with `sudo apt install ffmpeg`)\n\n\n## Usage\n\nRun the tool with:\n\n```console\nuvx trainscribe --folder /path/to/audio/folder [options]\n```\n\n```console\nTranscribe a folder of audio files to metadata.csv using Whisper.\n\noptions:\n  -h, --help            show this help message and exit\n  --folder, -f FOLDER   Folder with audio files\n  --lang, -l LANG       Language code for transcription (e.g. 'en')\n  --model, -m MODEL     Whisper model name (tiny, base, small, medium, large, turbo)\n  --speaker, -s SPEAKER\n                        Speaker label to add to metadata lines\n  --device, -d DEVICE   Device for whisper model (cuda/cpu)\n  --output, -o OUTPUT\n```\n\n### Example\nTranscribe English audio in dataset/wavs using the medium model:\n\n```console\nuvx trainscribe --folder dataset/wavs --lang en --model medium \n```\n\nThis generates `dataset/wavs/metadata.csv` \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveralvx%2Ftrainscribe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fveralvx%2Ftrainscribe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveralvx%2Ftrainscribe/lists"}