Bioacoustics

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Overview

Bioacoustics studies animal sounds and soundscapes to identify species, detect calls, track behavior, and investigate communication and ecosystem change. Common approaches include spectrogram-based CNNs and transformers, pretrained audio representations, self-supervised and weakly supervised learning, and methods for localizing calls or separating them from noise. Researchers use these tools with passive acoustic monitoring, annotated datasets, active learning, and compact models for field sensors, while also probing what learned representations reveal about vocal structure. A central challenge is reliable transfer across species, sites, sensors, and recording conditions, especially when labels are scarce and performance on curated benchmarks may not reflect field use.

Latest papers

CardsList

64 papers11 papers in the last four weeks, up 10% on the four weeks before. 0.1% of all new papers.

  1. Detecting and measuring respiratory events in horses during exercise with a microphone: deep learning vs. standard signal processing

    Aug 4, 2025Jeanne I. M. Parmentier, Rhana M. Aarts, Elin Hernlund +2Temporal Convolutional NetworksSound Event Detection

    Utrecht University · University of Twente · Inertia Technology B.V +5

  2. OpenBEATs: A Fully Open-Source General-Purpose Audio Encoder

    Jul 18, 2025Shikhar Bharadwaj, Samuele Cornell, Kwanghee Choi +4Audio Representation LearningAudio QA

    Carnegie Mellon University, USA · National Institute of Advanced Industrial Science and Technology (AIST), Japan

  3. Localized time-frequency representation learning for bioacoustic classification in complex soundscapes

    Feb 19, 2025Simen Hexeberg, Mandar Chitre, Matthias Hoffmann-Kuhnt +1BioacousticsAudio Classification

    ARL, Tropical Marine Science Institute, National University of Singapore · Department of Electrical & Computer Engineering, National University of Singapore · National Parks Board, Singapore

  4. Classifying bioacoustic data without individual call annotations using temporal convolutional networks and feature extractors

    Oct 22, 2024Laia Garrobé Fonollosa, Douglas Gillespie, Lina Stankovic +2BioacousticsPassive Acoustic Monitoring

    Sea Mammal Research Unit, School of Biology, University of St. Andrews, KY16 9TH, St. Andrews, Scotland · Electrical and Electronic Engineering, University of Strathclyde, Montrose Street, Glasgow, G1 1XJ, Scotland · Electrical and Electronic Engineering, University of Strathclyde, George Street, Glasgow, G1 1XW, Scotland