异步分布式交互式遗传算法,用于创建反映多个用户感受的音乐旋律

Kota Nomura, M. Fukumoto
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引用次数: 3

摘要

在产品设计领域,为了强调产品的价值,在产品上加入用户的感受是很重要的。交互式进化计算(IEC)是一种搜索适合每个用户感受的最佳或更好的媒体内容的方法。在扩展IEC的能力方面,最近的一些研究将IEC应用于多用户问题。本研究旨在利用并行分布式交互遗传算法(Distributed Interactive Genetic Algorithm, DIGA),创造适合多使用者感受的音乐旋律。在该方法中,每个用户通过主观评价解候选进行一般的交互式遗传算法(IGA)过程。在某些代中,候选解决方案在用户之间交换。通过交流,每个用户都会受到其他用户感受的影响。作为这些过程的结果,获得适合所有用户的良好解决方案。我们进行了听力实验,考察了数字数据机在音乐旋律创作中的效率。10人作为受试者参与实验,2人同时参与IGA任务。实验结果表明,该算法在最终代中获得了更高的适应度,并且通过解的交换获得了相似的旋律。为了明确异步交换方法的效率,需要进一步进行包括同步条件的比较实验研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asynchronous distributed interactive genetic algorithm for creating music melody reflecting multiple users' feelings
In the area of product design, it is important that adding user's feelings on the products for emphasizing its value. Interactive Evolutionary Computation (IEC) is known as a method that searches optimal or better media contents suited for each user's feelings. In terms of expanding the ability of IEC, some recent studies applied IEC into problem of multiple users. This study aims to create music melody suited for multiple users' feelings by employing parallel Distributed Interactive Genetic Algorithm (DIGA). In this method, each of the users proceeds general Interactive Genetic Algorithm (IGA) process by evaluating solution candidates subjectively. In some generations, solution candidates are exchanged between the users. With the exchange, each of the users is affected by other users' feelings. As a result of these processes, obtaining good solution suited for all users. We conducted listening experiments for investigating efficiency of the DIGA for creation of music melody. Ten persons participated in the experiment as subjects, and pair of the subjects participated in the IGA task simultaneously. Experimental results show that higher fitness was obtained in the final generation, and similar melody was obtained through exchange of solutions. To clarify the efficiency of the exchange of the asynchronous method, further study with comparing experiment including conditions synchronous is needed.
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