Cited by 60Music and Audio ProcessingAnimal Vocal Communication and BehaviorSpeech Recognition and Synthesis

On-Bird Sound Recordings: Automatic Acoustic Recognition of Activities and Contexts

Open access
Stowell, Dan, Benetos, Emmanouil, Gill, Lisa F.·2017·IEEE/ACM Transactions on Audio, Speech, and Language Processing

Abstract

We introduce a novel approach to studying animal behavior and the context in which it occurs, through the use of microphone backpacks carried on the backs of individual free-flying birds. These sensors are increasingly used by animal behavior researchers to study individual vocalizations of freely behaving animals, even in the field. However, such devices may record more than an animal's vocal behavior, and have the potential to be used for investigating specific activities (movement) and context (background) within which vocalizations occur. To facilitate this approach, we investigate the automatic annotation of such recordings through two different sound scene analysis paradigms: A scene-classification method using feature learning, and an event-detection method using probabilistic latent component analysis. We analyze recordings made with Eurasian jackdaws (Corvus monedula) in both captive and field settings. Results are comparable with the state of the art in sound scene analysis; we find that the current recognition quality level enables scalable automatic annotation of audio logger data, given partial annotation, but also find that individual differences between animals and/or their backpacks limit the generalization from one individual to another. we consider the interrelation of “scenes” and “events” in this particular task, and issues of temporal resolution.

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Registry

Crossref · 10.1109/taslp.2017.2690565

Cites

33 of 33 references verified0 citation errors · 0 not checkable

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  • Studies in other taxa such as birds, mammals, amphibians and arthropods suggest the context of acoustic signal production is an important factor affecting the parameters of acoustic signals measured.

    “Studies in other taxa such as birds (Stowell et al. 2017), mammals (Feighny et al. 2006; Caselli et al. 2014), amphibians (Toledo et al. 2015) and arthropods (Fukutomi and Ogawa 2017; Dobai et al. 2018; Kerchev 2019) suggest the context of acoustic signal production is an important factor affecting the parameters of acoustic signals measured.”
  • Wearable acoustic tags can capture vocalizations, movement-generated sounds, and environmental noise, enabling automated inference of behavioural states such as flying, diving, or resting from acoustic patterns alone.

    “Wearable acoustic tags can capture not only vocalizations but also movement-generated sounds and environmental noise, enabling automated inference of behavioural states such as flying, diving, or resting from acoustic patterns alone”

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Research works printed but not linked: 1

  1. karl, 1987, An improved radio transmitter harness with a weak link to prevent snagging (nuevo arnés para colocar radiotransmisores en aves), Journal of Field Ornithology, 58, 73

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Authors
Stowell, D., Benetos, E., & Gill, L. F.
Affiliations
  • Queen Mary University of London (GB)
  • Max Planck Society (DE)
Venue
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Published
2017-06
Volume
25
Issue
6
Pages
1193-1206
ISSN
  • 2329-9290 (ISSN-L)
  • 2329-9304
OpenAlex
W2581706890
Cited by
60
References
33
Citations by year
2026: 3 · 2025: 8 · 2024: 2 · 2023: 3 · 2022: 6 · 2021: 8 · 2020: 6 · 2019: 13 · 2018: 8 · 2017: 3
FWCI
6.84
Type
journal article
Language
en
Open access
Locations
  • IEEE/ACM Transactions on Audio Speech and Language Processing (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
  • arXiv (Cornell University)
Funders
  • EPSRC Early Career Research Fellowship (EP/L020505/1)
  • U.K. Royal Academy of Engineering Research Fellowship (RF/128)
  • Max Planck Society
Topics
  • Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Developmental Biology › Animal Vocal Communication and Behavior
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
Keywords
animal vocalizations, scene classification, event detection, probabilistic latent component analysis, representation learning, Corvus monedula, animal behavior, free-flying birds, individual differences, temporal resolution

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