Título |
Improvement of accuracy in a sound synthesis method using Evolutionary Product Unit Networks |
Autores |
Dolores Redel-Macias, M. , FERNÁNDEZ NAVARRO, FRANCISCO DE ASÍS, Gutierrez, Pedro A. , Jose Cubero-Atienza, A. , Hervas-Martinez, Cesar |
Publicación externa |
Si |
Medio |
Expert Syst. Appl. |
Alcance |
Article |
Naturaleza |
Científica |
Cuartil JCR |
1 |
Cuartil SJR |
1 |
Impacto JCR |
1.96500 |
Impacto SJR |
1.30500 |
Fecha de publicacion |
01/04/2013 |
ISI |
000314737600006 |
DOI |
10.1016/j.eswa.2012.08.041 |
Abstract |
Auralization through binaural transfer path analysis and synthesis is a useful tool to analyze how contributions from different sources affect the perception of sound. This paper presents a novel model based on the auralization of sound sources through the study of the behavior of the system with respect to frequency. The proposed approach is a combined model using the airborne source quantification (ASQ) technique for low-mid frequencies (<= 2.5 kHz) and Evolutionary Product-Unit Neural Networks (EPUNNs) for high frequencies (>2.5 kHz), which improve overall accuracy. The accuracy of all models has been evaluated in terms of the Mean Squared Error (MSE) and the Standard Error of Prediction (SEP), the combined model obtaining the smallest value for high frequencies. Moreover, the best prediction model was established based on sound quality metrics, the proposed method showing better accuracy than the ASQ technique at high frequencies in terms of loudness, sharpness and 1/3rd octave bands. (C) 2012 Elsevier Ltd. All rights reserved. |
Palabras clave |
Airborne source quantification; Auralization; Sound synthesis; Sound quality; Evolutionary computation; Product Unit Neural Networks |
Miembros de la Universidad Loyola |
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