A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements

Olive S, Welti T, Khonsaripour O. A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements. In: AES Convention 143. Audio Engineering Society; 2017. Paper 9840. Available from: https://aes.org/publications/elibrary-page/?id=19237

@inproceedings{Olive2017_19237,
  author = {Olive, Sean and Welti, Todd and Khonsaripour, Omid},
  title = {{A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements}},
  booktitle = {AES Convention 143},
  note = {Paper 9840},
  year = {2017},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19237}
}

TY  - CPAPER
TI  - A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements
AU  - Olive, Sean
AU  - Welti, Todd
AU  - Khonsaripour, Omid
T2  - AES Convention 143
M1  - Paper 9840
PY  - 2017
DA  - 2017/10/06
UR  - https://aes.org/publications/elibrary-page/?id=19237
PB  - Audio Engineering Society
LA  - en
AB  - A series of controlled listening tests were conducted on 30 different models of in-ear (IE) headphones to measure their relative sound quality. A total of 71 listeners both trained and untrained rated the headphones on a 100-point preference scale using a multiple stimulus method with a hidden reference and low anchor. A virtual headphone test method was used wherein each headphone was simulated over a high-quality replicator headphone equalized to match their measured magnitude response. Leakage was monitored and eliminated for each subject. The results revealed both trained and untrained listeners preferred the hidden reference, which was the replicator headphone equalized to our new IE headphone target response curve. The further the other headphones deviated from the target response, the less they were preferred. Part two of this paper develops a statistical model that predicts the headphone preference ratings based on their acoustic measurements.
ER  -