CIFASIS   20631
CENTRO INTERNACIONAL FRANCO ARGENTINO DE CIENCIAS DE LA INFORMACION Y DE SISTEMAS
Unidad Ejecutora - UE
artículos
Título:
Noisy Speech Recognition Based on Combined Audio-Visual Classifiers
Autor/es:
LUCAS D. TERISSI; GONZALO D. SAD; JUAN CARLOS GÓMEZ; MARIANELA PARODI
Revista:
LECTURE NOTES IN COMPUTER SCIENCE
Editorial:
Springer
Referencias:
Año: 2015 vol. 8869 p. 43 - 53
ISSN:
0302-9743
Resumen:
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.