Lightweight package to validate/measure audio files in local or S3 directories.
Project description
Usage
1. Install
pip install dvtk
2. Run
Run dvtk to validate audio files in local directories.
dvtk \
--paths /path/to/directory/ \
--ext .wav \
--metrics dvtk.default_metrics:sr,duration,max_amplitude,dnsmos_speech \
--output dv_result.csv \
--parallel \
--max-workers 8
Run dvtk to validate audio files in S3 directories.
dvtk \
--paths s3://bucket-name/path/to/directory/ \
--ext .wav \
--metrics dvtk.default_metrics:sr,duration,max_amplitude,dnsmos_speech \
--output dv_result.csv \
--parallel \
--max-workers 8
Remarks
- You can specify multiple paths and extensions (e.g.,
--ext .wav .flac). - You can specify the AWS profile to use (
--aws-profile). - More default metrics are available in
dvtk.default_metrics(e.g., reference-free PESQ, reference-free SI-SDR for speech).
Using Custom Metrics
- Create a small python module (e.g.,
mymetrics.py) in your working directory:
# mymetrics.py
import numpy as np
def custom_metric(audio: np.ndarray, sr: int) -> float:
... # compute the custom metric
return metric # float
- Run the CLI:
dvtk \
--paths /path/to/directory/ \
--ext .wav \
--metrics dvtk.default_metrics:duration,max_amplitude,dnsmos_speech \
mymetrics:custom_metric \
--output dv_result.csv \
--parallel \
--max-workers 8
- Support more storage backends (e.g., Google Cloud Storage)
- On-disk caching or cehckpointing
- Progress bar
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