NDLI: Modified subspace method based on convex model for underdetermined blind speech separation

Content Provider	IEEE Xplore Digital Library
Author	Liangjun Zhang Jie Yang Kaiwang Lu Qingnian Zhang
Copyright Year	1975
Abstract	Recently, many researches have been done to solve the speech separation problems in the underdetermined cases, and the "Two-step" method is widely used, which estimates the mixing matrix first and then separates the sources. Subspace projection is an effective method for signal separation, whereas it has some limitations because it fixes the active number at the Time-Frequency (TF) point as a constant. A commonly used solution is to add an extra step to estimate the active source number at every TF point, which will increase the computation cost greatly. This paper provides a new convex-model-based subspace projection method with enhanced functionality, which can be used for Underdetermined Blind Source Separation (UBSS). The model takes into account both projection and size of the signal's subspace, without estimating the real source numbers at the TF points. Simulation results show that the proposed method overcomes the shortage of conventional subspace method and achieves higher separation performance. Furthermore, the proposed algorithm can be employed as a preprocessing technology in the fields of acoustic signals enhancement, recognition, and biomedical images, etc.
Sponsorship	IEEE Consumer Electronics Society
Starting Page	225
Ending Page	232
Page Count	8
File Size	464346
File Format	PDF
ISSN	00983063
Volume Number	60
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Estimation Noise Manganese Vectors Source separation Computational modeling convex model speech separation speech enhancement blind source separation subspace projection
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Media Technology

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