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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.08313 |
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| _version_ | 1866909950895194112 |
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| author | Ravizza, Gabriele Villegas, Julián Volk, Christer P. Stegenborg-Andersen, Tore Pei, Yan |
| author_facet | Ravizza, Gabriele Villegas, Julián Volk, Christer P. Stegenborg-Andersen, Tore Pei, Yan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_08313 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Adaptive Method for Target Curve Selection Ravizza, Gabriele Villegas, Julián Volk, Christer P. Stegenborg-Andersen, Tore Pei, Yan Audio and Speech Processing 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. |
| title | An Adaptive Method for Target Curve Selection |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2512.08313 |