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.
Página web: aquí