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Soundbay: Deep Learning Framework for Marine Mammals and Bioacoustic Research

2023/11/07 by Noam Bressler, Bressler, Noam, Michael E. Faran +9
Biochemistry, Genetics and Molecular Biology · Earth and Planetary Sciences · Environmental Science · #Animal Vocal Communication and Behavior #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Marine animal studies overview #Sound (cs.SD) #Underwater Acoustics Research #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2311.04343

openalex publication_date 2023/11/07 · openalex created_date 2023/11/10 · openalex updated_date 2026/07/28

Abstract

This paper presents Soundbay, an open-source Python framework that allows bio-acoustics and machine learning researchers to implement and utilize deep learning-based algorithms for acoustic audio analysis. Soundbay provides an easy and intuitive platform for applying existing models on one's data or creating new models effortlessly. One of the main advantages of the framework is the capability to compare baselines on different benchmarks, a crucial part of emerging research and development related to the usage of deep-learning algorithms for animal call analysis. We demonstrate this by providing a benchmark for cetacean call detection on multiple datasets. The framework is publicly accessible via https://github.com/deep-voice/soundbay

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