A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones

Olive S, Welti T, Khonsaripour O. A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones. In: AES Convention 144. Audio Engineering Society; 2018.pp. 9919:1-15. Available from: https://aes.org/publications/elibrary-page/?id=19436

@inproceedings{Olive2018_19436,
  author = {Olive, Sean and Welti, Todd and Khonsaripour, Omid},
  title = {{A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones}},
  booktitle = {AES Convention 144},
  pages = {9919:1-15},
  url = {https://aes.org/publications/elibrary-page/?id=19436},
  year = {2018},
  month = may,
  publisher = {Audio Engineering Society},
  address = {Milan Italy}
}

TY  - CPAPER
TI  - A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones
AU  - Olive, Sean
AU  - Welti, Todd
AU  - Khonsaripour, Omid
T2  - AES Convention 144
SP  - 1
EP  - 15
M1  - Paper 9919
PY  - 2018
DA  - 2018/05/06
UR  - https://aes.org/publications/elibrary-page/?id=19436
PB  - Audio Engineering Society
CY  - Milan Italy
LA  - en
AB  - A controlled listening test was conducted on 31 different models of around-ear (AE) and on-ear (OE) headphones to determine listeners’ sound quality preferences. One-hundred-thirty listeners both trained and untrained rated the headphones based on preference using a virtual headphone method that used a single replicator headphone equalized to match magnitude and minimum phase responses of the different headphones. Listeners rated seven different headphones in each trial that included high (the new Harman AE-OE target curve) and low anchors. On average, both trained and untrained listeners preferred the high anchor to 31 other choices. Using machine learning a model was developed that predicts the listeners’ headphone preference ratings of the headphones based on deviation in magnitude response from the Harman target curve.
ER  -