Evolutionary tuning of filters coefficients for binaural audio equalization. (June 2020)

• Record Type: Journal Article
• Authors: Pepe, Giovanni; Gabrielli, Leonardo; Squartini, Stefano; Cattani, Luca
• Is Part Of: Applied acoustics. Volume 163(2020)
• Publication Date: 2020-06
• Subjects: Evolutionary computation -- FIR filter design -- Audio equalization -- Automotive audio -- Particle swarm optimization -- Gravitational search algorithm; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2019.107204
• Languages: English
• ISSNs: 0003-682X

Abstract

Highlights: Innovative evolutionary approach for Multichannel Audio Equalization. Solutions based on Particle Swarm Optimization and Gravitational Search Algorithm. FIR filter coefficients are optimized according to a specific fitness function. Extensive experimental evaluation in a real automotive scenario. Proposed algorithms outperform state-of-art Audio Equalization techniques. Abstract: This paper presents a novel multichannel audio equalization technique based on evolutionary computation algorithms for tuning the filters coefficients. Specifically, two distinct evolutionary algorithms are used on purpose, i.e. the Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). Two alternative solutions for the definition of evolutionary particles have been devised and tested with both techniques. Given the desired frequency response, the fitness function is formulated in terms of amplitude spectral distance. These techniques have been assessed by computer experiments, conducted on a in-car binaural equalization scenario considering 7 loudspeakers and a binaural microphone. The obtained results show that the proposed solutions achieve a remarkably superior performance compared to the baseline methods, with a 5 times reduction of the mean square error in the amplitude spectral domain.