Synthesis of Non-Linguistic Utterances for Sound Design Support Using a Genetic Algorithm

Author:

Khota Ahmed1,Cooper Eric W.1,Yan Yu1

Affiliation:

1. Affective Engineering and Computer Arts Laboratory, Graduate School of Information Science and Engineering, Ritsumeikan University, 2-150 Iwakura-cho, Ibaraki 567-8570, Japan

Abstract

As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of non-speech sounds that can convey emotions has been limited. To enable social robots to use a large amount of non-speech sounds in a natural and dynamic way, while expressing a wide range of emotions effectively, this work proposes an automatic method of sound generation using a genetic algorithm, coupled with a random forest model trained on representative non-speech sounds to validate each produced sound’s ability to express emotion. The sounds were tested in an experiment wherein subjects rated the perceived valence and arousal. Statistically significant clusters of sounds in the valence arousal space corresponded to different emotions, showing that the proposed method generates sounds that can readily be used in social robots.

Publisher

MDPI AG

Reference32 articles.

1. Sound design for emotion and intention expression of socially interactive robots;Jee;Intell. Serv. Robot.,2010

2. Bethel, C., and Murphy, R. (2006, January 13–15). Auditory and other non-verbal expressions of affect for robots. Proceedings of the 2006 AAAI Fall Symposium, Washington, DC, USA.

3. Read, R. (2014). The Study of Non-Linguistic Utterances for Social Human-Robot Interaction. [Ph.D. Thesis, University of Plymouth].

4. Review of Semantic-Free Utterances in Social Human-Robot Interaction;Yilmazyildiz;Int. J. Hum. Comput. Interact.,2016

5. Sound Synthesis for Communicating Nonverbal Expressive Cues;Salichs;IEEE Access,2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3