Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/47594
Title: Automatic classification of frogs calls based on fusion of features and SVM
Authors: Noda Arencibia, Juan J.
Travieso, Carlos M. 
Sánchez-Rodríguez, David 
Dutta, Malay Kishore
Vyas, Garima
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Sound Classification
Frogs Call Recognition
Mfcc
Data Fusion
Svm
Issue Date: 2015
Journal: 2015 Eighth International Conference On Contemporary Computing (Ic3)
Conference: 8th International Conference on Contemporary Computing, IC3 2015 
Abstract: 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
Source: 2015 8th International Conference on Contemporary Computing, IC3 2015 (7346653), p. 59-63
Appears in Collections:Actas de congresos
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