Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/70040
Título: | Acoustic classification of singing insects based on MFCC/LFCC fusion | Autores/as: | Noda, Juan J. Travieso-González, Carlos M. Sánchez-Rodríguez, David Alonso-Hernández, Jesús B. |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Acoustic Monitoring Bioacoustic Taxonomy Identification Biological Acoustic Analysis Insect Sound Classification Support Vector Machine |
Fecha de publicación: | 2019 | Publicación seriada: | Applied Sciences (Basel) | Resumen: | 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 | Fuente: | Applied Sciences (Basel) [ISSN 2076-3417], v. 9 (19), 4097 |
Colección: | Artículos |
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