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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Peng Tianliang Chen Yang |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Inf. Sci. & Eng., Southeast Univ., Nanjing, China (Peng Tianliang; Chen Yang) |
| Abstract | Inverse Truncated Mixing Matrix (ITMM) is a powerful method for underdetermined instantaneous blind source separation [1]. In this paper, we generalize ITMM algorithm to underdetermined convolutive blind source separation case. The proposed algorithm can be divided into two steps. The first step is the mixing filters estimation. The convolutive mixture can become an instantaneous mixture in time-frequency (TF) domain under some narrowband assumptions. Then, we used cluster method to estimate mixing matrix in every frequency bin. The second step is the source recovery part, we used ITMM method to mixing matrix in every frequency bin to source recovery in TF domain. Experimental evaluations are gained in artificial Room Impulse Responses (RIRs) environments, compared with conventional algorithms, the ITMM algorithm can separate speech sources to a higher signal-to-interference ratio (SIR). |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 268316 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479989188 |
| e-ISBN | 9781479989201 |
| DOI | 10.1109/ICSPCC.2015.7338923 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-09-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Time-frequency analysis Time-frequency Underdetermined Convolutive blind source separation Clustering algorithms Estimation Inverse Truncated Mixing Matrix Speech Blind source separation Sensors Manganese |
| Content Type | Text |
| Resource Type | Article |
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