Abstract
Unsupervised speech separation refers to the task of separating the individual speaker's speech from the multi- speaker speech without using any apriori information regarding speakers. This paper mainly focuses on unsupervised speech separation for single and multichannel case. State of art speech separation algorithms based on statistical, auditory, and signal processing approaches are evaluated and results are discussed. Algorithms are evaluated for synthetic and real speech mixtures. Experimental results shows that multichannel speech separation algorithms perform better than single channel for artificial speech mixtures and for real speech mixtures the efficacy of signal processing approach compared with other two in terms of subjective evaluation.
Published Version
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.
