Several authors have shown that the sounds of anurans can be used as an indicator of climate change. For this purpose anuran sound automatic classification has become an important issue for biologists and other climate scientists. In this paper two approaches have been used to feature every sound frame: Mel Frequency Cepstral Coefficients (MFCC); and parameters based on the MPEG-7 standard. The methods to extract the features and to classify the sounds are described. Up to ten different classification algorithms have also been considered. Their results are compared using several metrics, mainly based on the classification error rate. The main conclusion is that both, the MFCC and the MPEG-7 parameters, are adequate for featuring and classifying anuran sounds, although MFCC get best metrics for more classifiers. When the number of parameters is an important concern, MPEG-7 features show better results. Additionally, from a qualitative point of view, MPEG-7 features are semantically richer than their MFCC counterparts.
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