论文标题
通过音乐驱动的机器人情绪韵律和手势建立人类机器人信任
Establishing Human-Robot Trust through Music-Driven Robotic Emotion Prosody and Gesture
论文作者
论文摘要
随着人类机器人协作机会的不断扩大，信任对于机器人的全面参与和利用变得越来越重要。情感信任，基于情感关系和人际交往尤其至关重要，因为它对错误更具弹性并增加了合作的意愿。在本文中，我们介绍了一个基于音乐驱动的情感韵律和手势，鼓励人们对机器人身份的感知，该模型旨在避免荒唐的山谷。人类音乐家生成并用情感信息标记了象征性音乐短语。这些短语控制着通过音素和电子仪器插值生成的合成引擎播放预渲染的音频样品。手势也由象征性短语驱动，编码从音乐短语到低自由度运动的情感。通过用户研究，我们表明我们的系统能够准确地向用户描绘一系列情绪。我们还表明，与使用最先进的文本到语音系统相比，我们的非语言音频产生的平均信任平均值高8％。
As human-robot collaboration opportunities continue to expand, trust becomes ever more important for full engagement and utilization of robots. Affective trust, built on emotional relationship and interpersonal bonds is particularly critical as it is more resilient to mistakes and increases the willingness to collaborate. In this paper we present a novel model built on music-driven emotional prosody and gestures that encourages the perception of a robotic identity, designed to avoid uncanny valley. Symbolic musical phrases were generated and tagged with emotional information by human musicians. These phrases controlled a synthesis engine playing back pre-rendered audio samples generated through interpolation of phonemes and electronic instruments. Gestures were also driven by the symbolic phrases, encoding the emotion from the musical phrase to low degree-of-freedom movements. Through a user study we showed that our system was able to accurately portray a range of emotions to the user. We also showed with a significant result that our non-linguistic audio generation achieved an 8% higher mean of average trust than using a state-of-the-art text-to-speech system.
