Perceptual Objective Audio Quality Assessment using Computational Auditory Model (POAQ-CAM)

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Date

2019-11

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Addis Ababa University

Abstract

Audio quality assessment is one of the key considerations in television and radio broadcasting systems. Up until now, in many Ethiopian broadcasting service providers, the only way to measure the audio quality of an end to end broadcasting system is by using the human subjective evaluation method. Even though subjective evaluation is the ideal method for assessing the audio quality, it is time-consuming and even more challenging for real-time audio quality monitoring. We, therefore, require an objective measurement method that can quantitatively estimate the perceptual audio quality based on the physical features of the audio signal. Consequently, the idea of substituting the subjective evaluation by objective, computer-based methods has been an ongoing focus of research and development. Several methods for making objective perceptual measurement of audio quality have been introduced and standardized during the last decade; however, most approaches have accuracy issues. To solve these problems an improved intrusive objective audio quality estimation system has been proposed based on a psychoacoustically validated computational human auditory model and based on the framework of the VISQOLAudio audio quality assessment metric. This thesis evaluates the performance of the proposed model, POAQ-CAM, against the latest ViSQOLAudio, PEAQb and PEMO-Q models using a large database of audio and speech subjective listening tests that were originally carried out by International Telecommunication Union (ITU), CoreSV and TCD-VOIP. Compared to the above models, the proposed estimation system has a considerable improvement both in terms of accuracy, measured using root mean square error (RMSE) and linearity measured based on the correlation coefficient. The RMSE values of POAQ-CAM are reduced by 22.65%, 43.1% and 48.1% with respect to ViSQOLAudio, PEMO-Q and PEAQb models, while the

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Keywords

POAQ-CAM, Audio quality assessment, Computational auditory model

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