{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:28:45Z","timestamp":1760146125552,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T00:00:00Z","timestamp":1728172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Biodiversity Fund of the Federal Ministry of Austria for Climate Action, Environment, Energy, Mobility, Innovation and Technology and Next Generation EU","award":["C321025"],"award-info":[{"award-number":["C321025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Machine learning approaches for pattern recognition are increasingly popular. However, the underlying algorithms are often not open source, may require substantial data for model training, and are not geared toward specific tasks. We used open-source software to build a green toad breeding call detection algorithm that will aid in field data analysis. We provide instructions on how to reproduce our approach for other animal sounds and research questions. Our approach using 34 green toad call sequences and 166 audio files without green toad sounds had an accuracy of 0.99 when split into training (70%) and testing (30%) datasets. The final algorithm was applied to amphibian sounds newly collected by citizen scientists. Our function used three categories: \u201cGreen toad(s) detected\u201d, \u201cNo green toad(s) detected\u201d, and \u201cDouble check\u201d. Ninety percent of files containing green toad calls were classified as \u201cGreen toad(s) detected\u201d, and the remaining 10% as \u201cDouble check\u201d. Eighty-nine percent of files not containing green toad calls were classified as \u201cNo green toad(s) detected\u201d, and the remaining 11% as \u201cDouble check\u201d. Hence, none of the files were classified in the wrong category. We conclude that it is feasible for researchers to build their own efficient pattern recognition algorithm.<\/jats:p>","DOI":"10.3390\/info15100610","type":"journal-article","created":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T07:30:18Z","timestamp":1728286218000},"page":"610","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An Easily Customizable Approach for Automated Species-Specific Detection of Anuran Calls Using the European Green Toad as an Example"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5638-7924","authenticated-orcid":false,"given":"Lukas","family":"Landler","sequence":"first","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8596-8728","authenticated-orcid":false,"given":"Yurii V.","family":"Kornilev","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"},{"name":"National Museum of Natural History, Bulgarian Academy of Sciences, 1 Tsar Osvoboditel Blvd., 1000 Sofia, Bulgaria"}]},{"given":"Stephan","family":"Burgstaller","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6537-1441","authenticated-orcid":false,"given":"Janette","family":"Siebert","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"given":"Maria","family":"Krall","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4953-0534","authenticated-orcid":false,"given":"Magdalena","family":"Spie\u00dfberger","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2056-4084","authenticated-orcid":false,"given":"Daniel","family":"D\u00f6rler","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0083-4908","authenticated-orcid":false,"given":"Florian","family":"Heigl","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology and Biodiversity Research, Institute of Zoology, BOKU University, 1180 Vienna, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,6]]},"reference":[{"key":"ref_1","first-page":"25","article-title":"Pattern Recognition Techniques: A Review","volume":"3","author":"Asht","year":"2012","journal-title":"Int. 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