Visual Features for Lithuanian Phone Recognition

Abstract

Paper presents visual features for speech recognition. Visual speech recognition can be applied as the support for the acoustical recognition process or as a standalone speech recognition approach in the case of absence of the acoustical data. Static geometrical features of the speaker's lips were used for recognition. Statistical analysis of the feature values enabled us to select individual feature for each analyzed phone and the combined feature set for all phones. The discriminative power was tested using Bayes classification rule. 4th order analysis enabled us to recognize phones with the average rate of 60.3 %, the highest recognition rate of 81.3 % was achieved identifying phone [o].