The Belfast storytelling database: A spontaneous social interaction database with laughter focused annotation

G. McKeown, W. Curran, J. Wagner, F. Lingenfelser, E. André
{"title":"The Belfast storytelling database: A spontaneous social interaction database with laughter focused annotation","authors":"G. McKeown, W. Curran, J. Wagner, F. Lingenfelser, E. André","doi":"10.1109/ACII.2015.7344567","DOIUrl":null,"url":null,"abstract":"To support the endeavor of creating intelligent interfaces between computers and humans the use of training materials based on realistic human-human interactions has been recognized as a crucial task. One of the effects of the creation of these databases is an increased realization of the importance of often overlooked social signals and behaviours in organizing and orchestrating our interactions. Laughter is one of these key social signals; its importance in maintaining the smooth flow of human interaction has only recently become apparent in the embodied conversational agent domain. In turn, these realizations require training data that focus on these key social signals. This paper presents a database that is well annotated and theoretically constructed with respect to understanding laughter as it is used within human social interaction. Its construction, motivation, annotation and availability are presented in detail in this paper.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"30 1","pages":"166-172"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACII.2015.7344567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

Abstract

To support the endeavor of creating intelligent interfaces between computers and humans the use of training materials based on realistic human-human interactions has been recognized as a crucial task. One of the effects of the creation of these databases is an increased realization of the importance of often overlooked social signals and behaviours in organizing and orchestrating our interactions. Laughter is one of these key social signals; its importance in maintaining the smooth flow of human interaction has only recently become apparent in the embodied conversational agent domain. In turn, these realizations require training data that focus on these key social signals. This paper presents a database that is well annotated and theoretically constructed with respect to understanding laughter as it is used within human social interaction. Its construction, motivation, annotation and availability are presented in detail in this paper.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
贝尔法斯特讲故事数据库:一个以笑声为中心的自发社会互动数据库
为了支持在计算机和人类之间创建智能接口的努力,基于现实的人机交互的培训材料的使用已被认为是一项至关重要的任务。创建这些数据库的影响之一是,人们越来越意识到,在组织和协调我们的互动过程中,经常被忽视的社会信号和行为的重要性。笑是这些关键的社交信号之一;它在维持人类交互的流畅性方面的重要性直到最近才在具体化的会话代理领域显现出来。反过来,这些实现需要关注这些关键社会信号的训练数据。这篇论文提出了一个数据库,在理解人类社会互动中使用的笑声方面进行了很好的注释和理论构建。本文详细介绍了它的结构、动机、注释和可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Avatar and participant gender differences in the perception of uncanniness of virtual humans Neural conditional ordinal random fields for agreement level estimation Fundamental frequency modeling using wavelets for emotional voice conversion Bimodal feature-based fusion for real-time emotion recognition in a mobile context Harmony search for feature selection in speech emotion recognition
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1