声学和行为启发式用于快速交互式声音设计
Ava Souaille1, Vincent Lostanlen1, Mathieu Lagrange1
1Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes, France.
PloS one
|January 2, 2024
概括
本研究引入了启发式设计,以减少交互式声音设计中的设计空间,使该过程更有效率. 通过使用代用模型,设计师可以更快地获得更好的结果,特别是对于复杂的任务,如创建电动汽车声音.
科学领域:
- 人与计算机的交互
- 声学工程 声学工程
- 计算设计的计算设计.
背景情况:
- 在设计中收集用户反至关重要,但往往耗时且昂贵.
- 交互式音响设计面临由于设计空间庞大,人体试验有限的效率低下风险.
- 优化像愉悦性和可检测性这样的感知品质需要有效地探索设计变化的变化.
研究的目的:
- 提出和评估用于减少交互式优化过程中的设计空间的启发式.
- 调查替代模型在近似感知量方面的有效性,以优化设计.
- 加快交互式设计的融合,特别是对于具有大搜索空间的任务.
主要方法:
- 开发启发式利用替代模型来近似感知量.
- 使用遗传算法对愉快和可检测的电动汽车声音的交互设计的应用.
- 基于声学描述符和基于行为数据的替代模型的比较.
主要成果:
- 启发式调整将设计空间减少了多达64倍,并将代减少了多达2倍,以获得相当的性能.
- 基于行为数据的替代模型产生了优越的整体设计改进.
- 基于声学描述符的模型需要仔细选择描述符才能有效.
结论:
- 拟议的启发式方法显著加快了交互式设计的融合.
- 替代模型,特别是那些基于行为数据的模型,在优化复杂的声音设计参数方面是有效的.
- 这种方法非常适用于由于时间或成本限制而无法进行详尽的搜索的应用.
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