bowdet 0.1.0

Bow change detection for bowed string instruments

bowdet

Bow change detection for bowed string instruments

bowdet detects bow changes in audio recordings of bowed string instruments (viola, violin, cello) using deep learning.

Installation

pip install bowdet

Quick Start

from bowdet import detect

# Detect bow changes (returns list of timestamps in seconds)
bow_changes = detect("recording.wav")
print(bow_changes)  # [1.23, 2.45, 3.67, ...]

Models

Model	IoU@0.1 F1	Speed	Size
MERT (default)	0.616	~2 min/min audio	378 MB
CNN	0.554	~30 sec/min audio	5 MB

Parameters

detect(
    audio_path,           # path to wav file
    model="mert",         # "mert" or "cnn"
    threshold=0.5,        # peak detection threshold (0-1)
    min_dist=0.35,        # minimum distance between bow changes (seconds)
                          # decrease for fast passages (e.g. spiccato): min_dist=0.2
                          # increase for slow passages (e.g. long bows): min_dist=0.5
)

Weights

Weights are downloaded automatically on first use (~380 MB for MERT). Cached at ~/.bowdet/weights/

Limitations

• Trained on 9 performers across diverse repertoire (Bach, Biber, Penderecki, Hindemith, etc.)
• Performance may degrade on playing styles significantly different from training data
• Evaluated on viola recordings; expected to generalize to violin and cello
• Designed for solo string instrument recordings; accompaniment or ensemble recordings may reduce accuracy

Citation

[paper pending]

License

MIT