Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/47594
Título: | Automatic classification of frogs calls based on fusion of features and SVM | Autores/as: | Noda Arencibia, Juan J. Travieso, Carlos M. Sánchez-Rodríguez, David Dutta, Malay Kishore Vyas, Garima |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Sound Classification Frogs Call Recognition Mfcc Data Fusion Svm |
Fecha de publicación: | 2015 | Publicación seriada: | 2015 Eighth International Conference On Contemporary Computing (Ic3) | Conferencia: | 8th International Conference on Contemporary Computing, IC3 2015 | Resumen: | This paper presents a new approach for the acoustic classification of frogs' calls using a novel fusion of features: Mel Frequency Cepstral Coefficients (MFCCs), Shannon entropy and syllable duration. First, the audio recordings of different frogs' species are segmented in syllables. For each syllable, each feature is extracted and the cepstral features (MFCC) are computed and evaluated separately as in previous works. Finally, the data fusion is used to train a multiclass Support Vector Machine (SVM) classifier. In our experiment, the results show that our novel feature fusion increase the classification accuracy; achieving an average of 94.21% ± 8,04 in 18 frog's species. | URI: | http://hdl.handle.net/10553/47594 | ISBN: | 9781467379489 | ISSN: | 2572-6110 | DOI: | 10.1109/IC3.2015.7346653 | Fuente: | 2015 8th International Conference on Contemporary Computing, IC3 2015 (7346653), p. 59-63 |
Colección: | Actas de congresos |
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