marl/crepe

Health v2 · maintenance only

Adoption not part of the score

1411 stars · 186 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CREPE is a monophonic pitch tracker based on a deep convolutional neural network that operates directly on time-domain audio waveforms, distributed as a Python package with a pre-trained TensorFlow/Keras model. It provides both a command-line utility and a Python API that output fundamental frequency (f0) and voicing confidence estimates over time.

Use cases

• estimate the pitch of a wav file
• extract fundamental frequency contours from monophonic audio
• track pitch of singing voice recordings
• get voicing confidence scores for audio frames
• compare pitch trackers like pYIN and SWIPE
• batch process audio files for f0 analysis from the command line

When to choose

• you need accurate monophonic pitch estimation on 16 kHz audio
• you want a pre-trained deep learning pitch tracker without training your own model
• you need both f0 values and voicing confidence per frame
• you prefer a simple CLI or Python API for audio analysis

When to avoid

• you need polyphonic pitch estimation for multi-instrument audio
• you cannot install TensorFlow or lack GPU/CPU resources for deep inference
• you need real-time low-latency pitch tracking in production
• you need a lightweight non-neural pitch tracker

Facets

library · maturity maintenance

machine-learning audio-processing cli machine-learning python cli cross-platform pitch-estimation monophonic-pitch-tracking tensorflow keras pretrained-model music-information-retrieval fundamental-frequency audio

Member repositories

For agents

markdown · JSON · MCP: product_card(name="marl/crepe")