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Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification
BACKGROUND: Bee colony sound is a continuous, low-frequency buzzing sound that varies with the environment or the colony’s behavior and is considered meaningful. Bees use sounds to communicate within the hive, and bee colony sounds investigation can reveal helpful information about the circumstances...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884476/ https://www.ncbi.nlm.nih.gov/pubmed/36721779 http://dx.doi.org/10.7717/peerj.14696 |
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author | Di, Nayan Sharif, Muhammad Zahid Hu, Zongwen Xue, Renjie Yu, Baizhong |
author_facet | Di, Nayan Sharif, Muhammad Zahid Hu, Zongwen Xue, Renjie Yu, Baizhong |
author_sort | Di, Nayan |
collection | PubMed |
description | BACKGROUND: Bee colony sound is a continuous, low-frequency buzzing sound that varies with the environment or the colony’s behavior and is considered meaningful. Bees use sounds to communicate within the hive, and bee colony sounds investigation can reveal helpful information about the circumstances in the colony. Therefore, one crucial step in analyzing bee colony sounds is to extract appropriate acoustic feature. METHODS: This article uses VGGish (a visual geometry group—like audio classification model) embedding and Mel-frequency Cepstral Coefficient (MFCC) generated from three bee colony sound datasets, to train four machine learning algorithms to determine which acoustic feature performs better in bee colony sound recognition. RESULTS: The results showed that VGGish embedding performs better than or on par with MFCC in all three datasets. |
format | Online Article Text |
id | pubmed-9884476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98844762023-01-30 Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification Di, Nayan Sharif, Muhammad Zahid Hu, Zongwen Xue, Renjie Yu, Baizhong PeerJ Agricultural Science BACKGROUND: Bee colony sound is a continuous, low-frequency buzzing sound that varies with the environment or the colony’s behavior and is considered meaningful. Bees use sounds to communicate within the hive, and bee colony sounds investigation can reveal helpful information about the circumstances in the colony. Therefore, one crucial step in analyzing bee colony sounds is to extract appropriate acoustic feature. METHODS: This article uses VGGish (a visual geometry group—like audio classification model) embedding and Mel-frequency Cepstral Coefficient (MFCC) generated from three bee colony sound datasets, to train four machine learning algorithms to determine which acoustic feature performs better in bee colony sound recognition. RESULTS: The results showed that VGGish embedding performs better than or on par with MFCC in all three datasets. PeerJ Inc. 2023-01-26 /pmc/articles/PMC9884476/ /pubmed/36721779 http://dx.doi.org/10.7717/peerj.14696 Text en ©2023 Di et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Agricultural Science Di, Nayan Sharif, Muhammad Zahid Hu, Zongwen Xue, Renjie Yu, Baizhong Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title | Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title_full | Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title_fullStr | Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title_full_unstemmed | Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title_short | Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification |
title_sort | applicability of vggish embedding in bee colony monitoring: comparison with mfcc in colony sound classification |
topic | Agricultural Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884476/ https://www.ncbi.nlm.nih.gov/pubmed/36721779 http://dx.doi.org/10.7717/peerj.14696 |
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