DrCoffey/DeepSqueak
DeepSqueak v3: Using Machine Vision to Accelerate Bioacoustics Research
This tool helps bioacoustics researchers analyze recordings of animal vocalizations, particularly rodent ultrasonic vocalizations. It takes audio files of animal sounds and automatically identifies and classifies different types of calls using machine vision. Scientists studying animal behavior or neuroscience would use this to accelerate their data analysis.
420 stars.
Use this if you need to quickly and accurately detect, categorize, and quantify animal vocalizations from large audio datasets.
Not ideal if you are working with non-audio data or require real-time, in-the-field detection without prior training.
Stars
420
Forks
101
Language
MATLAB
License
BSD-3-Clause
Category
Last pushed
Nov 18, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/DrCoffey/DeepSqueak"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
birdnet-team/BirdNET-Analyzer
BirdNET analyzer for scientific audio data processing.
tphakala/birdnet-go
Realtime BirdNET soundscape analyzer
birdnet-team/birdnet
A Python library for identifying bird species by their sounds.
ear-team/bambird
Unsupervised classification to improve the quality of a bird song recording dataset....
UCSD-E4E/PyHa
A repo designed to convert audio-based "weak" labels to "strong" intraclip labels. Provides a...