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Separating overlapping bat calls with a bi-directional long short-term memory network

Integrative Zoology 2022年第5期17卷 741-751页

作者： Kangkang ZHANG Tong LIU Shengjing SONG Xin ZHAO Shijun SUN Walter METZNER Jiang FENG Ying LIU Jilin Provincial Key Laboratory of Animal Resource Conservation and Utilization Northeast Normal UniversityChangchunChina School of Environment Northeast Normal UniversityChangchunChina Department of Integrative Biology and Physiology University of CaliforniaLos AngelesCaliforniaUSA Collage of Animal Science and Technology Jilin Agricultural UniversityChangchunChina Key Laboratory for Vegetation Ecology Ministry of EducationNortheast Normal UniversityChangchunChina

Acquiring clear acoustic signals is critical for the analysis of animal *** studies commonly face the problem of overlapping signals,which can impede the structural identification of vocal units,but there is currently no satisfactory *** study presents a bi-directional long short-term memory network to separate overlapping echolocation-communication calls of 6 different bat species and reconstruct *** separation quality was evaluated using 7 temporal-spectrum *** the echolocation pulses and syllables of communication calls in the overlapping signals were separated and parameter comparisons showed no significant difference and negligible deviation between the extracted and original *** analysis was conducted with separated echolocation calls from each bat species to provide an example of practical application of the separated and reconstructed *** result of clustering analysis showed high corrected rand index(82.79%),suggesting the reconstructed waveforms could be reliably used for species *** results demonstrate a convenient and automated approach for separating overlapping *** study extends the application of deep neural networks to separate overlapping animal sounds.

关键词： bat vocalizations bioacoustics deep neural networks overlapping calls sound separation

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