ArticleNature human behaviour2022
Deep neural network models of sound localization reveal how perception is adapted to real-world environments.
Article in Nature human behaviour, 2022. 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 29 papers.
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Who cites it
29 citing papers in PubMed, 81 citations in OpenAlex.
- Human perception of avian biodiversity in naturalistic auditory scenes.PLoS computational biology · 2026Article
- Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.PLoS computational biology · 2026Article
- Optimized feature gains explain and predict successes and failures of human selective listening.Nature human behaviour · 2026Article
- From sound to source: Human and model recognition of environmental sounds.bioRxiv : the preprint server for biology · 2026Article
- Behavioral engagement facilitates auditory neuron responses beyond their receptive fields.PLoS biology · 2026Article
- Incomplete binaural restoration in single-sided deafness treated with cochlear implants: insights from compensatory head-orienting behaviors.Frontiers in neuroscience · 2026Article
- Task-optimized models of sensory uncertainty reproduce human confidence judgments.bioRxiv : the preprint server for biology · 2025Article
- A deep learning framework for understanding cochlear implants.bioRxiv : the preprint server for biology · 2025Article
- Learning spatial hearing via innate mechanisms.PLoS computational biology · 2025Article
- The detection of algebraic auditory structures emerges with self-supervised learning.PLoS computational biology · 2025Article
- A multi-stage auditory model for binaural sound localization using the locally competitive algorithm.Scientific reports · 2025Article
- Ideal-observer model of human sound localization of sources with unknown spectrum.Scientific reports · 2025Article
- Learning to hear again with alternating cochlear frequency allocations.Scientific reports · 2025Article
- Models optimized for real-world tasks reveal the task-dependent necessity of precise temporal coding in hearing.Nature communications · 2024Article
- Noise schemas aid hearing in noise.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from multi-channel audio.bioRxiv : the preprint server for biology · 2024Article
- Models optimized for real-world tasks reveal the task-dependent necessity of precise temporal coding in hearing.bioRxiv : the preprint server for biology · 2024Article
- Snn and sound: a comprehensive review of spiking neural networks in sound.Biomedical engineering letters · 2024Review
- Sensory and Perceptual Decisional Processes Underlying the Perception of Reverberant Auditory Environments.eNeuro · 2024Article
- A maturational frequency discrimination deficit may explain developmental language disorder.Psychological review · 2024Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
2 authors at 1 institution in 2 countries.
Funding
Abstract
Mammals localize sounds using information from their two ears. Localization in real-world conditions is challenging, as echoes provide erroneous information and noises mask parts of target sounds. To better understand real-world localization, we equipped a deep neural network with human ears and trained it to localize sounds in a virtual environment. The resulting model localized accurately in realistic conditions with noise and reverberation. In simulated experiments, the model exhibited many features of human spatial hearing: sensitivity to monaural spectral cues and interaural time and level differences, integration across frequency, biases for sound onsets and limits on localization of concurrent sources. But when trained in unnatural environments without reverberation, noise or natural sounds, these performance characteristics deviated from those of humans. The results show how biological hearing is adapted to the challenges of real-world environments and illustrate how artificial neural networks can reveal the real-world constraints that shape perception.
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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.