首页|Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from mult i-channel audio
Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from mult i-channel audio
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NETL
NSTL
2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Understanding the behavioral and neural dynamics of social interactions is a go al of contemporary neuroscience. Many machine learning methods have emerged in r ecent years to make sense of complex video and neurophysiological data that resu lt from these experiments. Less focus has been placed on understanding how anima ls process acoustic information, including social vocalizations. "A critical step to bridge this gap is determining the senders and receivers of acoustic information in social interactions. While sound source localization (SS L) is a classic problem in signal processing, existing approaches are limited in their ability to localize animal-generated sounds in standard laboratory enviro nments. Advances in deep learning methods for SSL are likely to help address the se limitations, however there are currently no publicly available models, datase ts, or benchmarks to systematically evaluate SSL algorithms in the domain of bio acoustics. Here, we present the VCL Benchmark: the first large-scale dataset for benchmarking SSL algorithms in rodents.
NETL
NSTL
