Paper Info
Title
PEAQ compatible audio quality estimation using computational auditory model
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.
Year
DOI
Venue
2012
10.1007/978-3-642-34478-7_11
ICONIP (4)
Keywords
Field
DocType
peaq compatible audio quality,quality assessment,proposed estimation system,novel psychoacoustic model,improved objective audio quality,audio quality,computational auditory model,minmax-optimized mov selection algorithm,estimation system,mean square error,least-squares weight vector algorithm
Psychoacoustics,Pattern recognition,Computer science,Selection algorithm,Weight,Mean squared error,Sound quality,Speech recognition,Correlation,Artificial intelligence,Cognitive model,PEAQ
Conference
Volume
ISSN
Citations 
7666
0302-9743
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Jia Zheng100.68
Meng-Yao Zhu2153.58
Junwei He330.74
Xiaoqing Yu47511.53