CIFASIS   20631
CENTRO INTERNACIONAL FRANCO ARGENTINO DE CIENCIAS DE LA INFORMACION Y DE SISTEMAS
Unidad Ejecutora - UE
artículos
Título:
Audio-Visual Speech Recognition Scheme based on Wavelets and Random Forests Classification
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. 9423 p. 567 - 574
ISSN:
0302-9743
Resumen:
This paper describes an audio-visual speech recognition system based on wavelets and Random Forests. Wavelet multiresolution analysis is used to represent in a compact form the sequence of both acoustic and visual input parameters. Then, recognition is performed using Random Forests classification using the wavelet-based features as inputs. The efficiency of the proposed speech recognition scheme is evaluated over two audio-visual databases, considering acoustic noisy conditions. Experimental results show that a good performance is achieved with the proposed system, outperforming the efficiency of traditional Hidden Markov Model-based approaches. The proposed system has only one tuning parameter, however, experimental results also show that this parameter can be selected within a small range without significantly changing the recognition results.