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A. Czyzewski, A. Ciarkowski, B. Kostek, J. Kotus, K. Lopatka, and P. Suchomski, "Adaptive Personal Tuning of Sound in Mobile Computers," J. Audio Eng. Soc., vol. 64, no. 6, pp. 405-428, (2016 June.). doi: https://doi.org/10.17743/jaes.2016.0014 A. Czyzewski, A. Ciarkowski, B. Kostek, J. Kotus, K. Lopatka, and P. Suchomski, "Adaptive Personal Tuning of Sound in Mobile Computers," J. Audio Eng. Soc., vol. 64 Issue 6 pp. 405-428, (2016 June.). doi: https://doi.org/10.17743/jaes.2016.0014
Abstract: An integrated methodology for enhancing audio quality in mobile computers is presented, whose key features are adapting the acoustic track to changing acoustic conditions of the environment, and matching audio characteristics to the users’ individual preferences. Signal processing algorithms included linearizing the frequency response, enhancing dialogue intelligibility, and adjusted dynamics to the users’ hearing characteristics. Algorithms were tested on two different computers (an All-in-one and a laptop), both of which were located in quiet office-like conditions but in the presence of strong noise. In general, test results showed that audio processing methods were useful tools for the improvement of the sound quality in compact computers. For example, although most the listeners were untrained, the processing for speech clarity in noise (dialogue enhancement and dynamics processing) yielded the highest scores. The majority of the results indicated that listeners perceive the processing as being desirable and useful.

@article{czyzewski2016adaptive,
author={czyzewski, andrzej and ciarkowski, andrzej and kostek, bozena and kotus, jozef and lopatka, kuba and suchomski, piotr},
journal={journal of the audio engineering society},
title={adaptive personal tuning of sound in mobile computers},
year={2016},
volume={64},
number={6},
pages={405-428},
doi={https://doi.org/10.17743/jaes.2016.0014},
month={june},} @article{czyzewski2016adaptive,
author={czyzewski, andrzej and ciarkowski, andrzej and kostek, bozena and kotus, jozef and lopatka, kuba and suchomski, piotr},
journal={journal of the audio engineering society},
title={adaptive personal tuning of sound in mobile computers},
year={2016},
volume={64},
number={6},
pages={405-428},
doi={https://doi.org/10.17743/jaes.2016.0014},
month={june},
abstract={an integrated methodology for enhancing audio quality in mobile computers is presented, whose key features are adapting the acoustic track to changing acoustic conditions of the environment, and matching audio characteristics to the users’ individual preferences. signal processing algorithms included linearizing the frequency response, enhancing dialogue intelligibility, and adjusted dynamics to the users’ hearing characteristics. algorithms were tested on two different computers (an all-in-one and a laptop), both of which were located in quiet office-like conditions but in the presence of strong noise. in general, test results showed that audio processing methods were useful tools for the improvement of the sound quality in compact computers. for example, although most the listeners were untrained, the processing for speech clarity in noise (dialogue enhancement and dynamics processing) yielded the highest scores. the majority of the results indicated that listeners perceive the processing as being desirable and useful.},}

TY - report
TI - Adaptive Personal Tuning of Sound in Mobile Computers
SP - 405 EP - 428
AU - Czyzewski, Andrzej
AU - Ciarkowski, Andrzej
AU - Kostek, Bozena
AU - Kotus, Jozef
AU - Lopatka, Kuba
AU - Suchomski, Piotr
PY - 2016
JO - Journal of the Audio Engineering Society
IS - 6
VO - 64
VL - 64
Y1 - June 2016 TY - report
TI - Adaptive Personal Tuning of Sound in Mobile Computers
SP - 405 EP - 428
AU - Czyzewski, Andrzej
AU - Ciarkowski, Andrzej
AU - Kostek, Bozena
AU - Kotus, Jozef
AU - Lopatka, Kuba
AU - Suchomski, Piotr
PY - 2016
JO - Journal of the Audio Engineering Society
IS - 6
VO - 64
VL - 64
Y1 - June 2016
AB - An integrated methodology for enhancing audio quality in mobile computers is presented, whose key features are adapting the acoustic track to changing acoustic conditions of the environment, and matching audio characteristics to the users’ individual preferences. Signal processing algorithms included linearizing the frequency response, enhancing dialogue intelligibility, and adjusted dynamics to the users’ hearing characteristics. Algorithms were tested on two different computers (an All-in-one and a laptop), both of which were located in quiet office-like conditions but in the presence of strong noise. In general, test results showed that audio processing methods were useful tools for the improvement of the sound quality in compact computers. For example, although most the listeners were untrained, the processing for speech clarity in noise (dialogue enhancement and dynamics processing) yielded the highest scores. The majority of the results indicated that listeners perceive the processing as being desirable and useful.