Best Student paper Award de la conférence internationale ASA2016

Marielle Malfante, Mauro Dalla Mura, Jerome I. Mars (Gispa-lab) and  Cedric Gervaise (Chaier Chorus),  Automatic fish sounds classification

The context of this work is environmental monitoring. We present an automatic fish sounds classification system. The solution we propose is new and based upon supervised machine learning (in particular, classification is performed by Random Forest).
The features used in input of the learning algorithm come from an extensive state of the art in various domains of classification such as speech, music, animal calls, environmental acoustic landscape, and human induced noises.
From this study, we propose to consider 66 different features (shape and/or statistical description in time and frequency). Fish sounds are automatically classified into four different classes and our system reaches 94% of correct classification rate compared to 77% when considering MFFC features.

http://acousticalsociety.org/content/spring-2016-meeting