ear-team/bambird
Unsupervised classification to improve the quality of a bird song recording dataset. https://doi.org/10.1016/j.ecoinf.2022.101952
This tool helps ecologists and ornithologists clean up large collections of bird song recordings. It takes raw audio files, often from public databases like Xeno-Canto, and automatically identifies specific bird sounds within them. The output is a refined dataset where each distinct bird call or song is accurately labeled and separated from background noise, making the data much more reliable for research or training AI models.
No commits in the last 6 months. Available on PyPI.
Use this if you need to quickly and accurately identify and isolate bird vocalizations within extensive audio datasets, reducing manual effort and improving data quality.
Not ideal if you are working with non-avian acoustic data or require very fine-grained, expert-level manual annotations for extremely rare or nuanced sounds.
Stars
31
Forks
7
Language
Python
License
BSD-3-Clause
Category
Last pushed
Jun 25, 2025
Commits (30d)
0
Dependencies
10
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