Abstract
The problem of blind audio source separation (BASS) in noisy and reverberant conditions is addressed by a novel approach, termed Global and LOcal Simplex Separation (GLOSS), which integrates full- and narrow-band simplex representations. We show that the eigenvectors of the correlation matrix between time frames in a certain frequency band form a simplex that organizes the frames according to the speaker activities in the corresponding band. We propose to build two simplex representations: one global based on a broad frequency band and one local based on a narrow band. In turn, the two representations are combined to determine the dominant speaker in each time-frequency (TF) bin. Using the identified dominating speakers, a spectral mask is computed and is utilized for extracting each of the speakers using spatial beamforming followed by spectral postfiltering. The performance of the proposed algorithm is demonstrated using real-life recordings in various noisy and reverberant conditions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE/ACM Transactions on Audio, Speech, and Language Processing
Disclaimer: 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.