For the first time in this paper we present results showing the effect of out of plane speaker head pose variation on a lip based speaker verification system. Using appearance DCT based features, we adopt a Mutual Information analysis technique to highlight the class discriminant DCT components most robust to changes in out of plane pose. Experiments are conducted using the initial phase of a new multi view Audio-Visual database designed for research and development of pose-invariant speech and speaker recognition. We show that verification performance can be improved by substituting higher order horizontal DCT components for vertical, particularly in the case of a train/test pose angle mismatch. We further show that the best performance can be achieved by combining this alternative feature selection with multi view training, reporting a relative 45% Equal Error Rate reduction over a common energy based selection.
Bibliographic reference. Pass, Adrian / Zhang, Jianguo / Stewart, Darryl (2010): "Feature selection for pose invariant lip biometrics", In INTERSPEECH-2010, 1165-1168.