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S. Goetze, E. Albertin, J. Rennies, EM. A.. Habets, and K. Kammeyer, "Speech Quality Assessment for Listening-Room Compensation," J. Audio Eng. Soc., vol. 62, no. 6, pp. 386-399, (2014 June.). doi: https://doi.org/10.17743/jaes.2014.0025 S. Goetze, E. Albertin, J. Rennies, EM. A.. Habets, and K. Kammeyer, "Speech Quality Assessment for Listening-Room Compensation," J. Audio Eng. Soc., vol. 62 Issue 6 pp. 386-399, (2014 June.). doi: https://doi.org/10.17743/jaes.2014.0025
Abstract: There is extensive research on listening-room compensation algorithms to remove the unwanted degradations of speech quality. Objective measures for quality assessment are required in order to evaluate such algorithms. They exist in two classes: reverberation-cancellation algorithms that equalize the room impulse response of the acoustic channel, and reverberation-suppression algorithms that remove the reverberant part of the speech signal by calculating the spectral weight for time-frequency coefficients. This paper focuses on evaluating the former. Algorithms are analyzed regarding their capability to assess reverberation, coloration, spectral distortion, perceived distance, and overall quality of the signals. An evaluation of the sound quality of the dereverberated signals is derived from subjective listening tests and then compared to objective measures.

@article{goetze2014speech,
author={goetze, stefan and albertin, eugen and rennies, jan and habets, emanuël a.p. and kammeyer, karl-dirk},
journal={journal of the audio engineering society},
title={speech quality assessment for listening-room compensation},
year={2014},
volume={62},
number={6},
pages={386-399},
doi={https://doi.org/10.17743/jaes.2014.0025},
month={june},} @article{goetze2014speech,
author={goetze, stefan and albertin, eugen and rennies, jan and habets, emanuël a.p. and kammeyer, karl-dirk},
journal={journal of the audio engineering society},
title={speech quality assessment for listening-room compensation},
year={2014},
volume={62},
number={6},
pages={386-399},
doi={https://doi.org/10.17743/jaes.2014.0025},
month={june},
abstract={there is extensive research on listening-room compensation algorithms to remove the unwanted degradations of speech quality. objective measures for quality assessment are required in order to evaluate such algorithms. they exist in two classes: reverberation-cancellation algorithms that equalize the room impulse response of the acoustic channel, and reverberation-suppression algorithms that remove the reverberant part of the speech signal by calculating the spectral weight for time-frequency coefficients. this paper focuses on evaluating the former. algorithms are analyzed regarding their capability to assess reverberation, coloration, spectral distortion, perceived distance, and overall quality of the signals. an evaluation of the sound quality of the dereverberated signals is derived from subjective listening tests and then compared to objective measures.},}

TY - paper
TI - Speech Quality Assessment for Listening-Room Compensation
SP - 386 EP - 399
AU - Goetze, Stefan
AU - Albertin, Eugen
AU - Rennies, Jan
AU - Habets, Emanuël A.P.
AU - Kammeyer, Karl-Dirk
PY - 2014
JO - Journal of the Audio Engineering Society
IS - 6
VO - 62
VL - 62
Y1 - June 2014 TY - paper
TI - Speech Quality Assessment for Listening-Room Compensation
SP - 386 EP - 399
AU - Goetze, Stefan
AU - Albertin, Eugen
AU - Rennies, Jan
AU - Habets, Emanuël A.P.
AU - Kammeyer, Karl-Dirk
PY - 2014
JO - Journal of the Audio Engineering Society
IS - 6
VO - 62
VL - 62
Y1 - June 2014
AB - There is extensive research on listening-room compensation algorithms to remove the unwanted degradations of speech quality. Objective measures for quality assessment are required in order to evaluate such algorithms. They exist in two classes: reverberation-cancellation algorithms that equalize the room impulse response of the acoustic channel, and reverberation-suppression algorithms that remove the reverberant part of the speech signal by calculating the spectral weight for time-frequency coefficients. This paper focuses on evaluating the former. Algorithms are analyzed regarding their capability to assess reverberation, coloration, spectral distortion, perceived distance, and overall quality of the signals. An evaluation of the sound quality of the dereverberated signals is derived from subjective listening tests and then compared to objective measures.