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JO. G.. Beerends, B. Busz, P. Oudshoorn, J. Van Vugt, K. Ahmed, and O. Niamut, "Degradation Decomposition of the Perceived Quality of Speech Signals on the Basis of a Perceptual Modeling Approach," J. Audio Eng. Soc., vol. 55, no. 12, pp. 1059-1076, (2007 December.). doi: JO. G.. Beerends, B. Busz, P. Oudshoorn, J. Van Vugt, K. Ahmed, and O. Niamut, "Degradation Decomposition of the Perceived Quality of Speech Signals on the Basis of a Perceptual Modeling Approach," J. Audio Eng. Soc., vol. 55 Issue 12 pp. 1059-1076, (2007 December.). doi:
Abstract: The authors discuss the way we perceive the quality of a speech signal and how different degradations contribute to the overall perceived speech (listening) quality. More specifically, ITU-T Recommendation P.862 (perceptual evaluation of speech quality—PESQ), which provides a perceptual modeling approach with which the subjectively perceived speech quality can be predicted, is used as a starting point for a degradation decomposition algorithm. This algorithm decomposes the perceived degradation into three different contributions by finding specific degradation indicators that quantify the impact of each type of degradation separately. The first degradation indicator quantifies the impact of additive noise as found in many speech-processing situations, such as when unwanted background noise is sent over a voice connection. The second degradation indicator quantifies the impact of linear timeinvariant frequency response distortions as, for example, introduced by a band-limited telephone system. The last degradation indicator quantifies the impact of the time-varying behavior of the system under test. This time response degradation indicator quantifies the impact of temporal signal loss, as found with packet loss in modern digital speech connections, and the impact of pulses (clicks) as found in many speech-processing systems.

@article{beerends2007degradation,
author={beerends, john g. and busz, bartosz and oudshoorn, paul and van vugt, jeroen and ahmed, kamal and niamut, omar},
journal={journal of the audio engineering society},
title={degradation decomposition of the perceived quality of speech signals on the basis of a perceptual modeling approach},
year={2007},
volume={55},
number={12},
pages={1059-1076},
doi={},
month={december},} @article{beerends2007degradation,
author={beerends, john g. and busz, bartosz and oudshoorn, paul and van vugt, jeroen and ahmed, kamal and niamut, omar},
journal={journal of the audio engineering society},
title={degradation decomposition of the perceived quality of speech signals on the basis of a perceptual modeling approach},
year={2007},
volume={55},
number={12},
pages={1059-1076},
doi={},
month={december},
abstract={the authors discuss the way we perceive the quality of a speech signal and how different degradations contribute to the overall perceived speech (listening) quality. more specifically, itu-t recommendation p.862 (perceptual evaluation of speech quality—pesq), which provides a perceptual modeling approach with which the subjectively perceived speech quality can be predicted, is used as a starting point for a degradation decomposition algorithm. this algorithm decomposes the perceived degradation into three different contributions by finding specific degradation indicators that quantify the impact of each type of degradation separately. the first degradation indicator quantifies the impact of additive noise as found in many speech-processing situations, such as when unwanted background noise is sent over a voice connection. the second degradation indicator quantifies the impact of linear timeinvariant frequency response distortions as, for example, introduced by a band-limited telephone system. the last degradation indicator quantifies the impact of the time-varying behavior of the system under test. this time response degradation indicator quantifies the impact of temporal signal loss, as found with packet loss in modern digital speech connections, and the impact of pulses (clicks) as found in many speech-processing systems.},}

TY - paper
TI - Degradation Decomposition of the Perceived Quality of Speech Signals on the Basis of a Perceptual Modeling Approach
SP - 1059 EP - 1076
AU - Beerends, John G.
AU - Busz, Bartosz
AU - Oudshoorn, Paul
AU - Van Vugt, Jeroen
AU - Ahmed, Kamal
AU - Niamut, Omar
PY - 2007
JO - Journal of the Audio Engineering Society
IS - 12
VO - 55
VL - 55
Y1 - December 2007 TY - paper
TI - Degradation Decomposition of the Perceived Quality of Speech Signals on the Basis of a Perceptual Modeling Approach
SP - 1059 EP - 1076
AU - Beerends, John G.
AU - Busz, Bartosz
AU - Oudshoorn, Paul
AU - Van Vugt, Jeroen
AU - Ahmed, Kamal
AU - Niamut, Omar
PY - 2007
JO - Journal of the Audio Engineering Society
IS - 12
VO - 55
VL - 55
Y1 - December 2007
AB - The authors discuss the way we perceive the quality of a speech signal and how different degradations contribute to the overall perceived speech (listening) quality. More specifically, ITU-T Recommendation P.862 (perceptual evaluation of speech quality—PESQ), which provides a perceptual modeling approach with which the subjectively perceived speech quality can be predicted, is used as a starting point for a degradation decomposition algorithm. This algorithm decomposes the perceived degradation into three different contributions by finding specific degradation indicators that quantify the impact of each type of degradation separately. The first degradation indicator quantifies the impact of additive noise as found in many speech-processing situations, such as when unwanted background noise is sent over a voice connection. The second degradation indicator quantifies the impact of linear timeinvariant frequency response distortions as, for example, introduced by a band-limited telephone system. The last degradation indicator quantifies the impact of the time-varying behavior of the system under test. This time response degradation indicator quantifies the impact of temporal signal loss, as found with packet loss in modern digital speech connections, and the impact of pulses (clicks) as found in many speech-processing systems.