TY - GEN
T1 - Adaptive weighting parameter in audio-visual voice activity detection
AU - Buchbinder, Matar
AU - Buchris, Yaakov
AU - Cohen, Israel
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2017/1/4
Y1 - 2017/1/4
N2 - Audio-visual voice activity detectors are traditionally based on fixed algorithms and do not consider the quality of the signals in each modality. This could significantly decrease the detector's performance in cases when one of the signals is relatively of poor quality. We proposed an improved solution, which evaluates the signal's quality in each modality and weights them accordingly. In this paper, we present a method for estimating the video quality, particularly in the presence of noisy motion vectors or global motion of the camera. The fussy motion vectors are intended to simulate blurred, unfocused video or low resolution sensor. An adaptive setting of the weighting parameter between the audio and the video signals ensures an optimal bimodal detector. The proposed method was incorporated with an audio-visual voice activity detector, and was tested with a real data set. Simulation results have shown an improved performance compared to the existing fixed method.
AB - Audio-visual voice activity detectors are traditionally based on fixed algorithms and do not consider the quality of the signals in each modality. This could significantly decrease the detector's performance in cases when one of the signals is relatively of poor quality. We proposed an improved solution, which evaluates the signal's quality in each modality and weights them accordingly. In this paper, we present a method for estimating the video quality, particularly in the presence of noisy motion vectors or global motion of the camera. The fussy motion vectors are intended to simulate blurred, unfocused video or low resolution sensor. An adaptive setting of the weighting parameter between the audio and the video signals ensures an optimal bimodal detector. The proposed method was incorporated with an audio-visual voice activity detector, and was tested with a real data set. Simulation results have shown an improved performance compared to the existing fixed method.
UR - http://www.scopus.com/inward/record.url?scp=85014277726&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICSEE.2016.7806124
DO - https://doi.org/10.1109/ICSEE.2016.7806124
M3 - منشور من مؤتمر
T3 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
BT - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
T2 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Y2 - 16 November 2016 through 18 November 2016
ER -