Aplicação de metaheurísticas no desenvolvimento de um modelo de otimização para o processo de codificação de áudio do Sistema Brasileiro de Televisão Digital

Abstract

The perceptual quality achieved by audio encoders depends directly on the choice of its parameters. The MPEG-4 AAC (Advanced Audio Coding), used in the Brazilian Digital Television System (BDTS), has a step in its structure that consists in iteration loop to choose the parameters of the encoder dynamically during the encoding process. This selection process can be defined as a problem of Operational Research, being a Part Selection Problem, termed as AAC Encoding Problem. The structure in the reference encoder not solves this problem optimally. Thus, this paper proposes the development and implementation of a model simulation of a structure, to find the internal parameters of the MPEG-4 AAC audio encoder, so as to optimize the perceptual audio quality for a given bit rate. The implementation of the optimization framework was developed in ANSI C programming language, using the Tabu Search and Genetic Algorithm metaheuristics in a hybrid structure. Through the minimization of the ANMR (Average Noise-to-Mask Ratio) metric, the algorithm tries to identify the best configuration of internal parameters of the MPEG-4 AAC. The results obtained using the optimization hybrid structure achieve lower values for the ANMR metric, i.e., an better perceptual audio quality, compared with the obtained with the reference encoder MPEG-4 AAC.