TY - GEN
T1 - New analytical update rule for TDOA inference for underdetermined BSS in noisy environments
AU - Maruyama, Takuro
AU - Araki, Shoko
AU - Nakatani, Tomohiro
AU - Miyabe, Shigeki
AU - Yamada, Takeshi
AU - Makino, Shoji
AU - Nakamura, Atsushi
PY - 2012
Y1 - 2012
N2 - In this paper, we propose a new technique for sparseness-based underdetermined BSS that is based on the clustering of the frequency-dependent time difference of arrival (TDOA) information and that can cope with diffused noise environments. Such a method with an EM algorithm has already been proposed, however, it required a time-consuming exhaust search for TDOA inference. To remove the need for such an exhaust search, we propose a new technique by focusing on a stereo case. We derive an update rule for analytical TDOA estimation. This update rule eliminates the need for the exhaustive TDOA search, and therefore reduces the computational load. We show experimental results for separation performance and calculation time in comparison with those obtained with the conventional approach. Our reported results validate our proposed method, that is, our proposed method achieves high performance without a high computational cost.
AB - In this paper, we propose a new technique for sparseness-based underdetermined BSS that is based on the clustering of the frequency-dependent time difference of arrival (TDOA) information and that can cope with diffused noise environments. Such a method with an EM algorithm has already been proposed, however, it required a time-consuming exhaust search for TDOA inference. To remove the need for such an exhaust search, we propose a new technique by focusing on a stereo case. We derive an update rule for analytical TDOA estimation. This update rule eliminates the need for the exhaustive TDOA search, and therefore reduces the computational load. We show experimental results for separation performance and calculation time in comparison with those obtained with the conventional approach. Our reported results validate our proposed method, that is, our proposed method achieves high performance without a high computational cost.
KW - EM algorithm
KW - speech sparseness
KW - time-frequency masking
KW - Underdetermined blind source separation
UR - http://www.scopus.com/inward/record.url?scp=84867616530&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867616530&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2012.6287869
DO - 10.1109/ICASSP.2012.6287869
M3 - Conference contribution
AN - SCOPUS:84867616530
SN - 9781467300469
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 269
EP - 272
BT - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
T2 - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Y2 - 25 March 2012 through 30 March 2012
ER -