ArticleJournal of the Royal Society, Interface2022
Automated identification of chicken distress vocalizations using deep learning models.
Article in Journal of the Royal Society, Interface, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- AI-Powered Vocalization Analysis in Poultry: Systematic Review of Health, Behavior, and Welfare Monitoring.Sensors (Basel, Switzerland) · 2025Pooled it
- Brains, quacks, and boojums: a review of neurotransmitter and neuroendocrine bases of welfare and enrichment in poultry with an emphasis on the Pekin duck.Poultry science · 2026Review
- Chicken disease detection and localization using multi-noise separation and acoustic recognition.Poultry science · 2026Article
- Classification of Goat Vocalization via Lightweight Machine Learning and High-Dimensional Acoustic Features.Animals : an open access journal from MDPI · 2026Article
- Artificial intelligence in precision poultry farming: opportunities, challenges, and future features.Animal frontiers : the review magazine of animal agriculture · 2026Article
- Leveraging artificial intelligence in bioacoustics for animal health monitoring and early diagnosis in veterinary medicine.Frontiers in veterinary science · 2026Review
- Automatic detection for bioacoustic research: a practical guide from and for biologists and computer scientists.Biological reviews of the Cambridge Philosophical Society · 2025Review
- Machine learning algorithms can predict emotional valence across ungulate vocalizations.iScience · 2025Article
- Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis.PloS one · 2025Article
- Humans can identify reward-related call types of chickens.Royal Society open science · 2024Article
- Who is calling? Optimizing source identification from marmoset vocalizations with hierarchical machine learning classifiers.Journal of the Royal Society, Interface · 2023Article
- Acoustic Monitoring of Professionally Managed Marine Mammals for Health and Welfare Insights.Animals : an open access journal from MDPI · 2023Review
- Precision Livestock Farming Research: A Global Scientometric Review.Animals : an open access journal from MDPI · 2023Review
- Automated identification of chicken distress vocalizations using deep learning models.Journal of the Royal Society, Interface · 2022Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The annual global production of chickens exceeds 25 billion birds, which are often housed in very large groups, numbering thousands. Distress calling triggered by various sources of stress has been suggested as an 'iceberg indicator' of chicken welfare. However, to date, the identification of distress calls largely relies on manual annotation, which is very labour-intensive and time-consuming. Thus, a novel convolutional neural network-based model, light-VGG11, was developed to automatically identify chicken distress calls using recordings (3363 distress calls and 1973 natural barn sounds) collected on an intensive farm. The light-VGG11 was modified from VGG11 with significantly fewer parameters (9.3 million versus 128 million) and 55.88% faster detection speed while displaying comparable performance, i.e. precision (94.58%), recall (94.89%), F1-score (94.73%) and accuracy (95.07%), therefore more useful for model deployment in practice. To additionally improve light-VGG11's performance, we investigated the impacts of different data augmentation techniques (i.e. time masking, frequency masking, mixed spectrograms of the same class and Gaussian noise) and found that they could improve distress calls detection by up to 1.52%. Our distress call detection demonstration on continuous audio recordings, shows the potential for developing technologies to monitor the output of this call type in large, commercial chicken flocks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.