Speaker identification using optimal lip biometrics
Preety Singh, Vijay Laxmi, Manoj Singh Gaur · 2012
Biometric identification systems rely on various features for identification. Visual mouth dynamics can aid speaker recognition where the audio modality is missing or of degraded quality. This paper proposes a method of reducing the visual feature set used in a speaker-recognition system. Geometric features extracted from the lip contour are reduced using the Minimum Redundancy Maximum Relevance (MRMR) method. It is observed that MRMR features give a best accuracy of 94.7%. A small feature set reduces computation time and storage overheads. Words from a given vocabulary are also tested for speaker recognition to check robustness of MRMR features for different words.