dc.contributor.author | De Camargo, Ulisses Moliterno | |
dc.contributor.author | Somervuo, Panu | |
dc.contributor.author | Ovaskainen, Otso | |
dc.date.accessioned | 2018-07-27T12:35:09Z | |
dc.date.available | 2018-07-27T12:35:09Z | |
dc.date.created | 2018-01-04T16:47:14Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | PLoS ONE. 2017, 12 (9). | nb_NO |
dc.identifier.issn | 1932-6203 | |
dc.identifier.uri | http://hdl.handle.net/11250/2506685 | |
dc.description.abstract | Autonomous audio recording is stimulating new field in bioacoustics, with a great promise for conducting cost-effective species surveys. One major current challenge is the lack of reliable classifiers capable of multi-species identification. We present PROTAX-Sound, a statistical framework to perform probabilistic classification of animal sounds. PROTAX-Sound is based on a multinomial regression model, and it can utilize as predictors any kind of sound features or classifications produced by other existing algorithms. PROTAX-Sound combines audio and image processing techniques to scan environmental audio files. It identifies regions of interest (a segment of the audio file that contains a vocalization to be classified), extracts acoustic features from them and compares with samples in a reference database. The output of PROTAX-Sound is the probabilistic classification of each vocalization, including the possibility that it represents species not present in the reference database. We demonstrate the performance of PROTAX-Sound by classifying audio from a species-rich case study of tropical birds. The best performing classifier achieved 68% classification accuracy for 200 bird species. PROTAX-Sound improves the classification power of current techniques by combining information from multiple classifiers in a manner that yields calibrated classification probabilities. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Public Library of Science | nb_NO |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | PROTAX-Sound: A probabilistic framework for automated animal sound identification | nb_NO |
dc.title.alternative | PROTAX-Sound: A probabilistic framework for automated animal sound identification | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 15 | nb_NO |
dc.source.volume | 12 | nb_NO |
dc.source.journal | PLoS ONE | nb_NO |
dc.source.issue | 9 | nb_NO |
dc.identifier.doi | 10.1371/journal.pone.0184048 | |
dc.identifier.cristin | 1536169 | |
dc.description.localcode | © 2017 de Camargo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | nb_NO |
cristin.unitcode | 194,66,10,0 | |
cristin.unitname | Institutt for biologi | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |