Evaluation of the Processing Times in Anuran Sound Classification

Nowadays, sound classification applications are becoming more common in the Wireless Acoustic Sensor Networks (WASN) scope. However, these architectures require special considerations, like looking for a balance between transmitted data and local processing. This article proposes an audio processing and classification scheme, focusing on WASN architectures. This article also analyzes in detail the time efficiency of the different stages involved (from acquisition to classification). This study provides useful information which makes it possible to choose the best tradeoff between processing time and classification result accuracy. This approach has been evaluated on a wide set of anurans songs registered in their own habitat. Among the conclusions of this work, there is an emphasis on the disparity in the classification and feature extraction and construction times for the different studied techniques, all of them notably depending on the overall feature number used.

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