In order to avoid the high cost of subjective listening tests for evaluating sound quality, objective assessment methods based on psychoacoustics have been routinely used. This research explores an assessment method for evaluating high-quality, multichannel audio codecs with a model that incorporates five monaural Model Output Variables (MOV) combined with four novel MOVs for predicting degradation of spatial attributes. When trained and verified with a listening-test data base of high-quality audio codecs, the model was able to predict small amounts of perceptual differences between test and reference signals in both spatial and timbre qualities.
Seo, Jeong-Hun; Chon, Sang Bae; Sung, Keong-Mo; Choi, Inyong
Affiliations: Institute of New Media and Communications, School of Electrical Engineering and Computer Science, Seoul National University, Republic of Korea; Multimedia R & D Team, DMC R & D Center, Samsung Electronics, Suwon, Republic of Korea; Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA, USA(See document for exact affiliation information.)
JAES Volume 61 Issue 7/8 pp. 535-545; July 2013
Publication Date: August 22, 2013
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