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Perception-Based Automatic Classification of Background Noise in Super-Wideband Telephony

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Given the effort required to perform subjective tests of quality of service in super-wideband telephone networks, an objective model of perceived degradation was created. This paper describes an efficient classification model of background noise arising at the originating side of super-wideband telephony. Classification depends on the impact on the perceived voice quality at receiving side from originating noises. This approach extends the research findings of narrowband telephony. Subjective experiments showed that background noises can be divided into three relevant classes: environmental noise, breath noise, and crackling noise. Each of these corresponds respectively to spectral flow, acoustic power variations, and the noise spectral centroid. Based on three quality degradation indicators, tests showed 82% correct classification of unknown noise signals.

JAES Volume 62 Issue 11 pp. 776-781; November 2014
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