Noisy Speech Recognition Based on Combined Audio-Visual Classifiers

Abstract

An isolated word speech recognition system based on audio-visual features is proposed in this paper. To enhance the recognition over different noisy conditions, this system combines three classifiers based on audio, visual and audio-visual information, respectively. The performance of the proposed recognition system is evaluated over two isolated word audio-visual databases, a public one and a database compiled by the authors of this paper. Experimental results show that the structure of the proposed system leads to significant improvements of the recognition rates through a wide range of signal-to-noise ratios.