Detalle del congreso

Autores: Lucas D. Terissi; Gonzalo D. Sad; Juan Carlos Gómez; Marianela Parodi.

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 thisparameter can be selected within a small range without significantly changing the recognition results.

Tipo de reunión: Congreso.

Tipo de trabajo: Artículo Completo.

Producción: Audio-Visual Speech Recognition Scheme based on Wavelets and Random Forests Classification.

Reunión científica: XX Iberoamerican Congress on Pattern Recognition (CIARP 2015).

Lugar: Montevideo.

Institución organizadora: Facultad de Ingeniería, Universidad de la República.

Publicado: Sí

Lugar publicación: Montevideo

Mes de reunión: 11

Año: 2015.

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