地理学 (GeSTICS):用于研究双方交互中的手势合成与语境化语音的多式体
Gaoussou Youssouf Kebe1, Mehmet Deniz Birlikci1, Auriane Boudin2
1Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
概括
GeSTICS数据集捕获来自体育采访的多式联络数据,以建模个人和情境因素如何影响共同语音手势和面部表情,以改善虚拟代理沟通.
科学领域:
- 人与计算机的交互
- 多式联运通信 多式联运通信
- 情感计算是一种情感计算.
背景情况:
- 有效的人与代理的互动需要现实的非语言行为.
- 现有的数据集往往缺乏全面的上下文线索,如个人和情境因素.
- 模拟语言,非语言和上下文线索的相互作用对于自然的共同语言手势和面部表情至关重要.
研究的目的:
- 介绍GeSTICS数据集,这是一个新的多式联运数据库.
- 促进对影响非语言沟通的个人和情境因素的研究.
- 在虚拟代理和人机交互系统中增强现实的非语言行为.
主要方法:
- 在比赛后的体育采访中收集了147名受访者的视听录音.
- 捕获的语音数据 (转录,词汇,声学特征) 和视觉数据 (身体姿势,面部表情).
- 包含了个人因素 (年龄,文化背景) 和情境因素 (游戏结果) 的元数据.
主要成果:
- 初步分析显示,语音特征对共同语音手势的影响是由情境和个人因素调节的.
- 证明了语境对沟通的说话和听话阶段的影响.
- 强调在非语言行为生成中考虑个人和情境细微差别的重要性.
结论:
- "GeSTICS数据集"为研究多式联络提供了宝贵的资源.
- 了解上下文因素是改善人与代理互动中非语言行为生成的关键.
- 数据集和分析代码是公开的,以促进虚拟代理和人机交互的研究.
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