Target Curve Selection by Differential Evolution

Ravizza G, Villegas J, Volk CP, Stegenborg-Andersen T, Pei Y. Target Curve Selection by Differential Evolution. In: 2025 AES International Conference on Headphone Technology. Audio Engineering Society; 2025. Paper 23. Available from: https://aes.org/publications/elibrary-page/?id=22949

@inproceedings{Ravizza2025_22949,
  author = {Ravizza, Gabriele and Villegas, Julian and Volk, Christer P. and Stegenborg-Andersen, Tore and Pei, Yan},
  title = {{Target Curve Selection by Differential Evolution}},
  booktitle = {2025 AES International Conference on Headphone Technology},
  note = {Paper 23},
  year = {2025},
  month = aug,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22949}
}

TY  - CPAPER
TI  - Target Curve Selection by Differential Evolution
AU  - Ravizza, Gabriele
AU  - Villegas, Julian
AU  - Volk, Christer P.
AU  - Stegenborg-Andersen, Tore
AU  - Pei, Yan
T2  - 2025 AES International Conference on Headphone Technology
M1  - Paper 23
PY  - 2025
DA  - 2025/08/18
UR  - https://aes.org/publications/elibrary-page/?id=22949
PB  - Audio Engineering Society
LA  - en
AB  - In this paper, we introduce an adaptation of the Interactive Differential Evolution (IDE) algorithm to the audio domain for the task of identifying the preferred over-the-ear headphone frequency response target among consumers. The method is based on data collection using an adaptive paired rating listening test paradigm (paired comparison with a scale). The IDE algorithm and its parameters are explained in detail. Additionally, data collected from three listening experiments with more than 20 consumers is presented, and the algorithm's performance in this untested domain is investigated on the basis of two convergence measures. The results indicate that this method can converge and may ease the task of 'extracting' frequency response preference from untrained consumers.
ER  -