Evaluation of Stereophonic Images with Listening Tests and Model Simulations

Kang KO, Nelson P, Park M. Evaluation of Stereophonic Images with Listening Tests and Model Simulations. In: AES Convention 124. Audio Engineering Society; 2008. Paper 7463. Available from: https://aes.org/publications/elibrary-page/?id=14593

@inproceedings{Kang2008_14593,
  author = {Kang, Kyeong Ok and Nelson, Philip and Park, Munhum},
  title = {{Evaluation of Stereophonic Images with Listening Tests and Model Simulations}},
  booktitle = {AES Convention 124},
  note = {Paper 7463},
  year = {2008},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=14593}
}

TY  - CPAPER
TI  - Evaluation of Stereophonic Images with Listening Tests and Model Simulations
AU  - Kang, Kyeong Ok
AU  - Nelson, Philip
AU  - Park, Munhum
T2  - AES Convention 124
M1  - Paper 7463
PY  - 2008
DA  - 2008/05/06
UR  - https://aes.org/publications/elibrary-page/?id=14593
PB  - Audio Engineering Society
LA  - en
AB  - A binaural hearing model has recently been suggested for the evaluation of the performance of virtual acoustic imaging systems. The model considers excitation-inhibition (EI) cell activity patterns as the internal representation of sound localisation cues, and a pattern-matching procedure with a frequency-weighting scheme produces the estimate of source location in the horizontal plane. Given the reasonable prediction of some important features in human sound localisation and lateralisation, this paper presents a further verification and application of the model in actual listening tests. In this work, participants' responses to stereophonic images have been compared with the predictions of the model, individually established from the subject's own HRTF. Model predictions have been found to be both qualitatively and quantitatively consistent with the test results, and in particular, the agreement between 2 and 3\,kHz gave a good indication that, unlike some similar models, the current model can effectively incorporate both ITD and ILD information according to their relative importance.
ER  -