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NRI: FND: Creating Trust Between Groups of Humans and Robots Using a Novel Music Driven Robotic Emotion Generator

NRI：FND：使用新颖的音乐驱动机器人情感发生器在人类和机器人群体之间建立信任

基本信息

批准号：
1925178
负责人：
Gil Weinberg
金额：
$ 66.99万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-11-01 至 2023-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925178&HistoricalAwards=false
关键词：
NRI FND Creating Trust Between

项目摘要

This project will perform fundamental research contributing to the establishment of trust between humans and robots through the development of novel emotional communication channels. As co-robots become prevalent at home, work, and public spaces, they need to become trust-worthy and socially believable agents if they are to be integrated into and accepted by society. The research will utilize the latest developments in Artificial Intelligence to gain knowledge about of the role of non-linguistic expressions in trust building. Findings from studies about non-linguistic emotional expressions such as prosody and gestures in music - one of the most emotionally meaningful human experiences - will be implemented in a group of newly developed personal robots. User experiments will be conducted to explore humans' reactions to - and trust building with - these prosody-driven robots. Results of the study will lead to novel approaches for creating open and meaningful interactions between groups of humans and robots. The research will advance national prosperity by increasing engagement, relatability, and trust in large scale human-robot interactive scenarios such as personal robots in private and public spaces, work place training, education, and combat. The project takes an interdisciplinary approach, which will address fields such as cognitive science, communication, and music, while leading to progress in both science and engineering.Prosodic features such as pitch, loudness, tempo, timbre, and rhythm bear strong resemblance to musical features, which can inform a novel approach for generative emotion-driven robotic prosody. The first phase of this project will focus on developing machine learning techniques to derive features from a newly created emotionally labeled musical dataset. It will use these features to drive a non-linguistic robotic voice synthesizer that conveys emotional content and builds trust. The results of this study will be integrated with previous work on conveying robotic emotions through physical gestures. The second phase of the project will focus on user experiments that will study subjects' preference to a variety of robotic emotional responses when interacting with a single robot. It will use the learned features to design a larger scale robotic emotional contagion engine in an effort to improve and enrich emotion-driven human interaction with large groups of robots.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将进行基础研究，通过开发新的情感沟通渠道，为建立人类和机器人之间的信任做出贡献。随着协作机器人在家庭、工作和公共场所变得普遍，如果它们要融入社会并被社会接受，它们需要成为值得信赖和社会可信的代理人。该研究将利用人工智能的最新发展来了解非语言表达在建立信任中的作用。关于非语言情感表达的研究结果，如音乐中的韵律和手势-最具情感意义的人类体验之一-将在一组新开发的个人机器人中实现。将进行用户实验，以探索人类对这些韵律驱动机器人的反应和信任建立。研究结果将为人类和机器人之间创造开放和有意义的互动提供新的方法。该研究将通过增加大规模人机交互场景中的参与度、相关性和信任度来促进国家繁荣，例如私人和公共空间中的个人机器人、工作场所培训、教育和战斗。该项目采用跨学科的方法，将涉及认知科学，通信和音乐等领域，同时导致科学和工程的进步。韵律特征，如音高，响度，克里思，音色和节奏与音乐特征有很强的相似性，这可以为生成情感驱动的机器人韵律提供新的方法。该项目的第一阶段将专注于开发机器学习技术，从新创建的情感标记音乐数据集中获取特征。它将使用这些功能来驱动一个非语言机器人语音合成器，传达情感内容并建立信任。这项研究的结果将与以前通过身体姿势传达机器人情感的工作相结合。该项目的第二阶段将专注于用户实验，研究受试者在与单个机器人互动时对各种机器人情感反应的偏好。它将使用学到的功能来设计一个更大规模的机器人情感感染引擎，以改善和丰富情感驱动的人类与大型机器人群体的互动。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Robot Gesture Sonification to Enhance Awareness of Robot Status and Enjoyment of Interaction

机器人手势语音化，增强机器人状态感知和互动乐趣

DOI：
10.1109/ro-man47096.2020.9223452
发表时间：
2020
期刊：
29th IEEE International Conference on Robot & Human Interactive Communication
影响因子：
0
作者：
Zahray, L: Savery
通讯作者：
Zahray, L: Savery

Musical Prosody-Driven Emotion Classification: Interpreting Vocalists Portrayal of Emotions Through Machine Learning

音乐韵律驱动的情感分类：通过机器学习解读歌手的情感描述