Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges
Biodiversity monitoring has become a critical task for governments and ecological research agencies for reducing significant loss of animal species. Existing monitoring methods are time-intensive and techniques such as tagging are also invasive and may adversely affect animals. Bioacoustics based mo...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9025054/ |
| _version_ | 1819001859618111488 |
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| author | Rama Rao K. V. S. N. James Montgomery Saurabh Garg Michael Charleston |
| author_facet | Rama Rao K. V. S. N. James Montgomery Saurabh Garg Michael Charleston |
| author_sort | Rama Rao K. V. S. N. |
| collection | DOAJ |
| description | Biodiversity monitoring has become a critical task for governments and ecological research agencies for reducing significant loss of animal species. Existing monitoring methods are time-intensive and techniques such as tagging are also invasive and may adversely affect animals. Bioacoustics based monitoring is becoming an increasingly prominent non-invasive method, involving the passive recording of animal sounds. Bioacoustics analysis can provide deep insights into key environmental integrity issues such as biodiversity, density of individuals and present or absence of species. However, analysing environmental recordings is not a trivial task. In last decade several researchers have tried to apply machine learning methods to automatically extract insights from these recordings. To help current researchers and identify research gaps, this paper aims to summarise and classify these works in the form of a taxonomy of the various bioacoustics applications and analysis approaches. We also present a comprehensive survey of bioacoustics data analysis approaches with an emphasis on bird species identification. The survey first identifies common processing steps to analyse bioacoustics data. As bioacoustics monitoring has grown, so does the volume of raw acoustic data that must be processed. Accordingly, this survey examines how bioacoustics analysis techniques can be scaled to work with big data. We conclude with a review of open challenges in the bioacoustics domain, such as multiple species recognition, call interference and automatic selection of detectors. |
| first_indexed | 2024-12-20T22:55:54Z |
| format | Article |
| id | doaj.art-b60b5165eb6c408d81fbd9837352ceb3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T22:55:54Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b60b5165eb6c408d81fbd9837352ceb32022-12-21T19:24:08ZengIEEEIEEE Access2169-35362020-01-018576845770810.1109/ACCESS.2020.29785479025054Bioacoustics Data Analysis – A Taxonomy, Survey and Open ChallengesRama Rao K. V. S. N.0https://orcid.org/0000-0002-9249-9114James Montgomery1Saurabh Garg2https://orcid.org/0000-0001-8719-284XMichael Charleston3School of Technology, Environments and Design, University of Tasmania, Hobart, TAS, AustraliaSchool of Technology, Environments and Design, University of Tasmania, Hobart, TAS, AustraliaSchool of Technology, Environments and Design, University of Tasmania, Hobart, TAS, AustraliaSchool of Natural Sciences, University of Tasmania, Hobart, TAS, AustraliaBiodiversity monitoring has become a critical task for governments and ecological research agencies for reducing significant loss of animal species. Existing monitoring methods are time-intensive and techniques such as tagging are also invasive and may adversely affect animals. Bioacoustics based monitoring is becoming an increasingly prominent non-invasive method, involving the passive recording of animal sounds. Bioacoustics analysis can provide deep insights into key environmental integrity issues such as biodiversity, density of individuals and present or absence of species. However, analysing environmental recordings is not a trivial task. In last decade several researchers have tried to apply machine learning methods to automatically extract insights from these recordings. To help current researchers and identify research gaps, this paper aims to summarise and classify these works in the form of a taxonomy of the various bioacoustics applications and analysis approaches. We also present a comprehensive survey of bioacoustics data analysis approaches with an emphasis on bird species identification. The survey first identifies common processing steps to analyse bioacoustics data. As bioacoustics monitoring has grown, so does the volume of raw acoustic data that must be processed. Accordingly, this survey examines how bioacoustics analysis techniques can be scaled to work with big data. We conclude with a review of open challenges in the bioacoustics domain, such as multiple species recognition, call interference and automatic selection of detectors.https://ieeexplore.ieee.org/document/9025054/Bioacousticsbiodiversitydensity estimationspecies identificationfeaturessyllables |
| spellingShingle | Rama Rao K. V. S. N. James Montgomery Saurabh Garg Michael Charleston Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges IEEE Access Bioacoustics biodiversity density estimation species identification features syllables |
| title | Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges |
| title_full | Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges |
| title_fullStr | Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges |
| title_full_unstemmed | Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges |
| title_short | Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges |
| title_sort | bioacoustics data analysis x2013 a taxonomy survey and open challenges |
| topic | Bioacoustics biodiversity density estimation species identification features syllables |
| url | https://ieeexplore.ieee.org/document/9025054/ |
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