Abstract
Determination of the number of sources is a practical issue that has to be addressed in applications of underdetermined blind source separation (UBSS). This paper proposes a noise-robust UBSS algorithm for highly overlapped speech sources in the short-time Fourier transform (STFT) domain. The basic principle of the proposed algorithm firstly estimates the unknown number of sources in time-frequency domain. Secondly, the original sources are recovered by a separation method using both sparseness and temporal structure. To mitigate the noise effect on the detection of auto-source TF points, we propose a method to effectively detect the auto-term locations of the sources by using the principal component analysis (PCA) of the STFTs of noisy mixtures.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
