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DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals
Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling sound...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900853/ https://www.ncbi.nlm.nih.gov/pubmed/36747788 http://dx.doi.org/10.1101/2023.01.24.525459 |
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author | Colligan, Thomas Irish, Kayla Emlen, Douglas J. Wheeler, Travis J. |
author_facet | Colligan, Thomas Irish, Kayla Emlen, Douglas J. Wheeler, Travis J. |
author_sort | Colligan, Thomas |
collection | PubMed |
description | Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling sound elements in recordings of animal sounds and demonstrate its utility on recordings of beetle courtships and whale songs. The software, DISCO, computes sensible confidence estimates and produces labels with high precision and accuracy. In addition to the core labeling software, it provides a simple tool for labeling training data, and a visual system for analysis of resulting labels. DISCO is open-source and easy to install, it works with standard file formats, and it presents a low barrier of entry to use. |
format | Online Article Text |
id | pubmed-9900853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-99008532023-02-07 DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals Colligan, Thomas Irish, Kayla Emlen, Douglas J. Wheeler, Travis J. bioRxiv Article Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling sound elements in recordings of animal sounds and demonstrate its utility on recordings of beetle courtships and whale songs. The software, DISCO, computes sensible confidence estimates and produces labels with high precision and accuracy. In addition to the core labeling software, it provides a simple tool for labeling training data, and a visual system for analysis of resulting labels. DISCO is open-source and easy to install, it works with standard file formats, and it presents a low barrier of entry to use. Cold Spring Harbor Laboratory 2023-01-26 /pmc/articles/PMC9900853/ /pubmed/36747788 http://dx.doi.org/10.1101/2023.01.24.525459 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Colligan, Thomas Irish, Kayla Emlen, Douglas J. Wheeler, Travis J. DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title | DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title_full | DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title_fullStr | DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title_full_unstemmed | DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title_short | DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
title_sort | disco: a deep learning ensemble for uncertainty-aware segmentation of acoustic signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900853/ https://www.ncbi.nlm.nih.gov/pubmed/36747788 http://dx.doi.org/10.1101/2023.01.24.525459 |
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