Abstract
Some algorithms based on Second Order Statistics (SOS) succeed in separating the non-stationary or colored mixing signals. Among those algorithms, the nonstationary signals are blocked, or the time delay is considerable for colored signals. The speech signal is non-stationary and colored. Based on the autocorrelation matrix of the delayed mixing signals in each block, a new algorithm to infer mixing speech signals is formulated. Since our algorithm covers both charactes of speech, the convergence of our algorithm needs fewer steps than those algorithms with only one characteristic; what’s more, the speed of our algorithm for separation is even faster than FastICA. Blind Signal Separation (BSS) experiment on speech signals under instantaneous mixing proves the effectiveness of our algorithm.
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.
