TY - GEN
T1 - Sound recognition in mixtures
AU - Nam, Juhan
AU - Mysore, Gautham J.
AU - Smaragdis, Paris
PY - 2012/2/27
Y1 - 2012/2/27
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84857263750&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857263750&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-28551-6_50
DO - 10.1007/978-3-642-28551-6_50
M3 - Conference contribution
AN - SCOPUS:84857263750
SN - 9783642285509
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 405
EP - 413
BT - Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings
T2 - 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012
Y2 - 12 March 2012 through 15 March 2012
ER -