Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/70040
Title: Acoustic classification of singing insects based on MFCC/LFCC fusion
Authors: Noda, Juan J.
Travieso-González, Carlos M. 
Sánchez-Rodríguez, David 
Alonso-Hernández, Jesús B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Acoustic Monitoring
Bioacoustic Taxonomy Identification
Biological Acoustic Analysis
Insect Sound Classification
Support Vector Machine
Issue Date: 2019
Journal: Applied Sciences (Basel) 
Abstract: This work introduces a new approach for automatic identification of crickets, katydids and cicadas analyzing their acoustic signals. We propose the building of a tool to identify this biodiversity. The study proposes a sound parameterization technique designed specifically for identification and classification of acoustic signals of insects using Mel Frequency Cepstral Coefficients (MFCC) and Linear Frequency Cepstral Coefficients (LFCC). These two sets of coefficients are evaluated individually as has been done in previous studies and have been compared with the fusion proposed in this work, showing an outstanding increase in identification and classification at species level reaching a success rate of 98.07% on 343 insect species.
URI: http://hdl.handle.net/10553/70040
ISSN: 2076-3417
DOI: 10.3390/app9194097
Source: Applied Sciences (Basel) [ISSN 2076-3417], v. 9 (19), 4097
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