Noisy Speech Recognition based on Combined Audio-Visual Classifiers

TERISSI, LUCAS DANIEL; SAD, GONZALO; GÓMEZ, JUAN CARLOS; PARODI, MARIANELA

Stockholm

Workshop; ICPR2014 satellite Workshop on Multimodal Pattern Recognition of Social Signals in Human Computer Interaction; 2014

International Associatio for Pattern Recognition

An isolated word speech recognition system based on audiovisual 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 a significant improvement of the recognition rates through a wide range of signal-to-noise ratios.