TAKESHI0\ogawa
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37f86d1

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CLI

WIP

Dataset

Dataset.bat webui (python webui_dataset.py) consists of slice audio and transcribe wavs.

Slice audio

python slice.py -i <input_dir> -o <output_dir> -m <min_sec> -M <max_sec>

Required:

  • input_dir: Path to the directory containing the audio files to slice.
  • output_dir: Path to the directory where the sliced audio files will be saved.

Optional:

  • min_sec: Minimum duration of the sliced audio files in seconds (default 2).
  • max_sec: Maximum duration of the sliced audio files in seconds (default 12).

Transcribe wavs

python transcribe.py -i <input_dir> -o <output_file> --speaker_name <speaker_name>

Required:

  • input_dir: Path to the directory containing the audio files to transcribe.
  • output_file: Path to the file where the transcriptions will be saved.
  • speaker_name: Name of the speaker.

Optional

  • --initial_prompt: Initial prompt to use for the transcription (default value is specific to Japanese).
  • --device: cuda or cpu (default: cuda).
  • --language: jp, en, or en (default: jp).
  • --model: Whisper model, default: large-v3
  • --compute_type: default: bfloat16

Train

Train.bat webui (python webui_train.py) consists of the following.

Preprocess audio

python resample.py -i <input_dir> -o <output_dir> [--normalize] [--trim]

Required:

  • input_dir: Path to the directory containing the audio files to preprocess.
  • output_dir: Path to the directory where the preprocessed audio files will be saved.

TO BE WRITTEN (WIP)

これいる?