TY - JOUR
T1 - NMF-based environmental sound source separation using time-variant gain features
AU - Innami, Satoshi
AU - Kasai, Hiroyuki
N1 - Funding Information:
This work was supported in part by the National Institute of Information and Communications Technology (NICT) , Japan, under the new generation network R&D program for innovative network virtualization platform and its application.
PY - 2012/9
Y1 - 2012/9
N2 - Various environmental sounds exist around us in our daily life. Recently, environmental sound recognition has drawn great attention for understanding our environment. However, because environmental sounds derive from multiple sound sources, it is difficult to recognize them accurately. If we were able to separate sound sources before sound recognition as a pre-process, then recognition would be easier and more accurate. We assume that monaural microphones are widely installed in mobile devices used as recording devices. This paper therefore presents a proposal for monaural sound source separation of environmental sounds. Two-phase clustering using non-negative matrix factorization (NMF) is proposed to separate monaural sound sources. In this proposal, the time-variant gain feature is used as an attribute of an environmental sound for more efficient sound separation.
AB - Various environmental sounds exist around us in our daily life. Recently, environmental sound recognition has drawn great attention for understanding our environment. However, because environmental sounds derive from multiple sound sources, it is difficult to recognize them accurately. If we were able to separate sound sources before sound recognition as a pre-process, then recognition would be easier and more accurate. We assume that monaural microphones are widely installed in mobile devices used as recording devices. This paper therefore presents a proposal for monaural sound source separation of environmental sounds. Two-phase clustering using non-negative matrix factorization (NMF) is proposed to separate monaural sound sources. In this proposal, the time-variant gain feature is used as an attribute of an environmental sound for more efficient sound separation.
KW - Acoustic signal analysis
KW - Audio source separation
KW - Blind source separation
KW - Clustering
KW - Environmental sound
KW - Non-negative matrix factorization
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U2 - 10.1016/j.camwa.2012.03.077
DO - 10.1016/j.camwa.2012.03.077
M3 - Article
AN - SCOPUS:84865687106
SN - 0898-1221
VL - 64
SP - 1333
EP - 1342
JO - Computers and Mathematics with Applications
JF - Computers and Mathematics with Applications
IS - 5
ER -