The Prediction of the Acceptability of Auditory Interference Based on Audibility

Baykaner K, Hummersone C, Mason R, Bech S. The Prediction of the Acceptability of Auditory Interference Based on Audibility. In: AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception. Audio Engineering Society; 2013. Paper 3-2. Available from: https://aes.org/publications/elibrary-page/?id=16908

@inproceedings{Baykaner2013_16908,
  author = {Baykaner, Khan and Hummersone, Christopher and Mason, Russell and Bech, Søren},
  title = {{The Prediction of the Acceptability of Auditory Interference Based on Audibility}},
  booktitle = {AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception},
  note = {Paper 3-2},
  year = {2013},
  month = sep,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16908}
}

TY  - CPAPER
TI  - The Prediction of the Acceptability of Auditory Interference Based on Audibility
AU  - Baykaner, Khan
AU  - Hummersone, Christopher
AU  - Mason, Russell
AU  - Bech, Søren
T2  - AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception
M1  - Paper 3-2
PY  - 2013
DA  - 2013/09/06
UR  - https://aes.org/publications/elibrary-page/?id=16908
PB  - Audio Engineering Society
LA  - en
AB  - In order to evaluate the ability of sound field control methods to generate independent listening zones within domestic and automotive environments, it is useful to be able to predict, without listening tests, the accept- ability of auditory interference scenarios. It was considered likely that a relationship would exist between masking thresholds and acceptability thresholds, thus a listening test was carried out to gather acceptability thresholds to compare with existing masking data collected under identical listening conditions. An analysis of the data revealed that a linear regression model could be used to predict acceptability thresholds, from only masking thresholds, with RMSE = 2.6 dB and R = 0.86. The same linear regression model was used to predict acceptability thresholds but with masking threshold predictions as the input. The results had RMSE = 4.2 dB and R = 0.88.
ER  -