Résumé
This paper presents a new system for water flow detection on real life recordings, and its application to medical context. The recognition system is based on an original feature for sound event detection in real life. This feature, called "spectral cover" shows an interesting behaviour to recognize water flow in a noisy environment. An experiment is realized with more than 7 hours of videos recorded by a wearable device. The system based on thresholds obtains good results for the water flow event recognition (Fmeasure of 66%). A comparison with classical approaches using MFCC or low levels descriptors and GMM classifiers is done to attest the good performance of our system. Adding the spectral cover to low levels descriptors also improve their performance and confirms the interest to this feature.