Sound Recognition in Mixtures

In this paper, we describe a method for recognizing sound sources in a mixture. While many audio-based content analysis methods focus on detecting or classifying target sounds in a discriminative manner, we approach this as a regression problem, in which we estimate the relative proportions of sound...

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Bibliographic Details
Published inLatent Variable Analysis and Signal Separation pp. 405 - 413
Main Authors Nam, Juhan, Mysore, Gautham J., Smaragdis, Paris
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2012
SeriesLecture Notes in Computer Science
Subjects
Relative Proportion
Single Source
Sound Source
Transition Matrice
Transition Matrix
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Summary:In this paper, we describe a method for recognizing sound sources in a mixture. While many audio-based content analysis methods focus on detecting or classifying target sounds in a discriminative manner, we approach this as a regression problem, in which we estimate the relative proportions of sound sources in the given mixture. Using source separation ideas based on probabilistic latent component analysis, we directly estimate these proportions from the mixture without actually separating the sources. We also introduce a method for learning a transition matrix to temporally constrain the problem. We demonstrate the proposed method on a mixture of five classes of sounds and show that it is quite effective in correctly estimating the relative proportions of the sounds in the mixture.
ISBN:9783642285509
3642285503
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-28551-6_50