A perceptual method is proposed for measuring harmonic distortion audibility. This method is similar to the CLEAR (Cepstral Loudness Enhanced Algorithm for Rub & buzz) algorithm previously proposed by the authors as a means of detecting audible Rub & Buzz, which is an extreme type of distortion [1,2]. Both methods are based on the Perceptual Evaluation of Audio Quality (PEAQ) standard [3]. In the present work, in order to estimate the audibility of regular harmonic distortion, additional psychoacoustic variables are added to the CLEAR algorithm. These variables are then combined using an artificial neural network approach to derive a metric that is indicative of the overall audible harmonic distortion. Experimental results on headphones are presented to justify the accuracy of the model.

Authors: Temme, Steve; Brunet, Pascal; Qarabaqi, Parastoo
Affiliation: Listen, Inc., Boston, MA, USA
AES Convention: 133 (October 2012) Paper Number: 8704
Publication Date: October 25, 2012
Subject: Measurement and Models

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