Consultation des notices

This master’s thesis is dedicated to the automatic classification of auditory scene using non-negative matrix factorization. A particular attention is paid to the performances achieved by the non-negative matrix factorization in sound sources detection. Our intuition was that a good classification could be achieve if we could efficiently detect the sources within auditory scenes. It appears on short artificial examples that taking into account the non-stationarity of the spectral content of the sound sources improves the source detection. Finally, our classification method is applied to a corpus of soundscapes of train stations and the results are compared with previous classifications methods. We finally conclude that using non-negative matrix factorization significantly improves the classification.