PEAQ compatible audio quality estimation using computational auditory model

Authors:
Jia Zheng;Mengyao Zhu;Junwei He;Xiaoqing Yu
Affiliations:
School of Communication & Information Engineering, Shanghai University, Shanghai, China;School of Communication & Information Engineering, Shanghai University, Shanghai, China;School of Communication & Information Engineering, Shanghai University, Shanghai, China;School of Communication & Information Engineering, Shanghai University, Shanghai, China
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
Year:
2012

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Abstract

This paper proposed an improved objective audio quality estimation system compatible with PEAQ (Perceptual Evaluation of Audio Quality). Based on the computational auditory model, we used a novel psychoacoustic model to assess the quality of highly impaired audio. We also applied the robust linear MOA (Least-squares Weight Vector algorithm) and MinmaxMOA (Minmax-Optimized MOV Selection algorithm) to cognitive model of the estimation system. Compared to the PEAQ advanced version, the proposed estimation system has a considerable improvement in performance both in terms of the correlation and MSE (Mean Square Error). By combining the computational auditory model and PEAQ, our estimation system can be applied to the quality assessment of highly impaired audio.