交互式差分进化在声音内容创造中的效率:与交互式遗传算法的比较

M. Fukumoto, Ryota Yamamoto, Shintarou Ogawa
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引用次数: 18

摘要

交互式进化计算(IEC)被认为是一种有效的方法来创建适合用户偏好和使用目标的媒体内容。其中,我们将差分进化这一最新的进化算法应用到IEC中。具体来说,我们已经提出了一种使用交互式差分进化(IDE)创建符号声音的方法。本研究旨在从根本上探讨IDE方法与交互式遗传算法(IGA)的有效性。实验1为IDE和IGA的创作实验,实验2为再评价实验。创造的目标是警告信号的声音。在实验2中,分别对IDE和IGA中产生的具有代表性的五音进行了评价。16名男性作为实验对象参加了实验。在实验1的结果中,IDE在主观适应度值上优于IGA。IGA的搜索空间明显缩小,IDE的搜索时间开销较大。在实验2的结果中,IDE的平均适应度值较高,但差异不显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Efficiency of Interactive Differential Evolution in Creation of Sound Contents: In Comparison with Interactive Genetic Algorithm
Interactive Evolutionary Computation (IEC) is well known as an effective method to create media contents suited to user's preference and objectives to use. As one of the methods, we have applied Differential Evolution, which is recent evolutionary algorithm to IEC. Concretely, we have already presented a method that creates sign sounds with Interactive Differential Evolution (IDE). This study aims to investigate fundamentally the efficacy of the IDE method in comparison with Interactive Genetic Algorithm (IGA). Two listening experiments were conducted: experiment 1 as a creation experiment with IDE and IGA, experiment 2 as a re-evaluation experiment. Target of the creation was warning sign sounds. In the experiment 2, representative five sign sounds created in both of IDE and IGA were evaluated. Sixteen males participated as subjects in the experiments. In the result of the experiment 1, IDE overcame IGA in subjective fitness value. Drastic shrink of searching space was observed in IGA, and larger time cost was observed in IDE. In the result of the experiment 2, higher fitness value in average was observed in IDE, however, the difference was not significant.
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