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Saliency-based modeling of acoustic scenes using sparse non-negative matrix factorization

: Cauchi, B.; Lagrange, M.; Misdariis, N.; Cont, A.


Institute of Electrical and Electronics Engineers -IEEE-:
14th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2013 : Paris, France 3-5 July 2013
Piscataway, NJ: IEEE, 2013
ISBN: 978-1-4799-0831-8
ISBN: 978-1-4799-0833-2
International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS) <14, 2013, Paris>
Conference Paper
Fraunhofer IDMT ()

The modeling of auditory scenes is a challenging task in Computational Auditory Scene Analysis. A method based on sparse Non-negative Matrix Factorization that can be used with no prior knowledge of the audio content to establish the similarity between scenes is proposed in this work. It is then evaluated on a corpus of soundscapes of train stations from a perceptual study and results are compared with the human perception. The proposed method, by being able to focus on salient events within the scene, achieves better performances than a state-of-the-art Bag-of-Frames approach though not reaching the human performances.