ArticleThe Journal of the Acoustical Society of America2019
Deep convolutional network for animal sound classification and source attribution using dual audio recordings.
Article in The Journal of the Acoustical Society of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 71 citations in OpenAlex.
- Developmental trajectories of vocal behaviors in common marmosets as a reference framework for neurobehavioral studies.Frontiers in neural circuits · 2026Article
- Leveraging artificial intelligence in bioacoustics for animal health monitoring and early diagnosis in veterinary medicine.Frontiers in veterinary science · 2026Review
- Animal Species Classification from Vocalizations Using Cochlear-Inspired Audio Features and Machine Learning.Biomimetics (Basel, Switzerland) · 2025Article
- Primate ACC encodes natural vocal interactions in a 'cocktail party'.bioRxiv : the preprint server for biology · 2025Article
- Automated detection of wolf howls using audio spectrogram transformers.Scientific reports · 2025Article
- Audio-Based Automatic Giant Panda Behavior Recognition Using Competitive Fusion Learning.Sensors (Basel, Switzerland) · 2025Article
- Deep Learning-Based Gender Recognition in Cherry Valley Ducks Through Sound Analysis.Animals : an open access journal from MDPI · 2024Article
- Propagating variational model uncertainty for bioacoustic call label smoothing.Patterns (New York, N.Y.) · 2024Article
- Neural network analysis of pharyngeal sounds can detect obstructive upper respiratory disease in brachycephalic dogs.PloS one · 2024Article
- BrachySound: machine learning based assessment of respiratory sounds in dogs.Scientific reports · 2023Article
- The neurobiology of vocal communication in marmosets.Annals of the New York Academy of Sciences · 2023Review
- Improving the workflow to crack Small, Unbalanced, Noisy, but Genuine (SUNG) datasets in bioacoustics: The case of bonobo calls.PLoS computational biology · 2023Article
- There You Are! Automated Detection of Indris' Songs on Features Extracted from Passive Acoustic Recordings.Animals : an open access journal from MDPI · 2023Article
- A Review of Automated Bioacoustics and General Acoustics Classification Research.Sensors (Basel, Switzerland) · 2022Review
- Introducing the Software CASE (Cluster and Analyze Sound Events) by Comparing Different Clustering Methods and Audio Transformation Techniques Using Animal Vocalizations.Animals : an open access journal from MDPI · 2022Article
- Review
- Article
- Utilizing DeepSqueak for automatic detection and classification of mammalian vocalizations: a case study on primate vocalizations.Scientific reports · 2021Article
- Article
- Deep Learning-Based Cattle Vocal Classification Model and Real-Time Livestock Monitoring System with Noise Filtering.Animals : an open access journal from MDPI · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
This paper introduces an end-to-end feedforward convolutional neural network that is able to reliably classify the source and type of animal calls in a noisy environment using two streams of audio data after being trained on a dataset of modest size and imperfect labels. The data consists of audio recordings from captive marmoset monkeys housed in pairs, with several other cages nearby. The network in this paper can classify both the call type and which animal made it with a single pass through a single network using raw spectrogram images as input. The network vastly increases data analysis capacity for researchers interested in studying marmoset vocalizations, and allows data collection in the home cage, in group housed animals.
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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.