Multimodal blind source separation for moving sources
Mohsen Naqvi
Yonggang Zhang
Jonathon Chambers
2134/5352
https://repository.lboro.ac.uk/articles/conference_contribution/Multimodal_blind_source_separation_for_moving_sources/9557189
A novel multimodal approach is proposed to solve the problem of
blind source separation (BSS) of moving sources. The challenge
of BSS for moving sources is that the mixing filters are time varying,
thus the unmixing filters should also be time varying, which are
difficult to track in real time. In the proposed approach, the visual
modality is utilized to facilitate the separation for both stationary and
moving sources. The movement of the sources is detected by a 3-D
tracker based on particle filtering. The full BSS solution is formed
by integrating a frequency domain blind source separation algorithm
and beamforming: if the sources are identified as stationary, a frequency
domain BSS algorithm is implemented with an initialization
derived from the visual information. Once the sources are moving,
a beamforming algorithm is used to perform real time speech
enhancement and provide separation of the sources. Experimental
results show that by utilizing the visual modality, the proposed algorithm
can not only improve the performance of the BSS algorithm
and mitigate the permutation problem for stationary sources, but also
provide a good BSS performance for moving sources in a low reverberant
environment.
2009-09-29 15:11:46
BSS
Multimodal signal processing
Particle filtering
3-D tracking
Beamforming
FastICA
Mechanical Engineering not elsewhere classified