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

该项目将进行基础研究，通过开发新的情感沟通渠道，为建立人与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，就需要成为值得信赖和社会可信的代理。该研究将利用人工智能的最新发展来了解非语言表达在信任建立中的作用。对非语言情感表达的研究结果，如音乐中的韵律和手势——这是最有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施。将进行用户实验，以探索人类对这些韵律驱动的机器人的反应和信任的建立。这项研究的结果将为人类和机器人群体之间创造开放和有意义的互动带来新的方法。该研究将通过增加大规模人机交互场景（如私人和公共空间、工作场所培训、教育和战斗中的个人机器人）的参与度、相关性和信任度，促进国家繁荣。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，同时在科学和工程方面取得进展。音高、响度、速度、音色和节奏等韵律特征与音乐特征非常相似，这可以为生成情感驱动的机器人韵律提供一种新的方法。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提取特征。它将利用这些功能来驱动一个非语言机器人语音合成器，以传达情感内容并建立信任。这项研究的结果将与之前通过肢体动作传达机器人情感的工作相结合。该项目的第二阶段将侧重于用户实验，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。它将利用学习到的特征来设计一个更大规模的机器人情感传染引擎，以改善和丰富人类与大型机器人群体之间的情感驱动互动。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.