Fuzzy Audio-Visual Feature Maps for Speaker Identification
Chibelushi, C.C. (2004) Fuzzy Audio-Visual Feature Maps for Speaker Identification. In: Applications and Science in Soft Computing. Springer-Verlag, Berlin, pp. 317-322.Full text not available from this repository.
Abstract or description
Speech-based person recognition by machine has not reached the level of technological maturity required by some of its potential applications. The deficiencies revolve around sub-optimal pre-processing, feature extraction or selection, and classification, particularly under conditions of input data variability. The joint use of audible and visible manifestations of speech aims to alleviate these shortcomings, but the development of effective combination techniques is challenging. This paper proposes and evaluates a combination approach for speaker identification based on fuzzy modelling of acoustic and visual speaker characteristics. The proposed audio-visual model has been evaluated experimentally on a speaker identification task. The results show that the joint model outperforms its isolated components in terms of identification accuracy. In particular, the cross-modal coupling of audio-visual streams is shown to improve identification accuracy.
|Item Type:||Book Chapter or Section|
|Subjects:||G400 Computer Science|
|Faculty:||Faculty of Computing, Engineering and Sciences > Computing|
|Depositing User:||Claude CHIBELUSHI|
|Date Deposited:||13 May 2013 23:07|
|Last Modified:||13 May 2013 23:07|
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