MEI机器人:利用母亲语言开发多模态情商

Angelica Lim, HIroshi G. Okuno
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引用次数: 45

摘要

我们介绍了一个名为MEI(多模态情商)的发展机器人的第一步,这个机器人可以通过语音、手势和步态来理解和表达情感,使用一个只接受语音训练的控制器。众所周知,人类可以感知声音、动作、音乐甚至是点光显示的影响,但人类是如何发展这种技能的尚不清楚。是天生的吗?如果不是,那么婴儿的情商是如何发展的呢?MEI机器人通过声音输入和对声音特征的感知映射来发展这些技能。我们将MEI的发展基于这样一种观点,即母亲语从很小的时候就被用作一种将动态声音轮廓与面部情绪联系起来的方式。MEI使用这些动态轮廓来理解和表达多模态情绪,使用一个称为SIRE(速度,强度,不规则性和范围)的统一模型。基于MEI的离线实验支持其跨模态泛化能力:用语音数据训练的模型可以识别完全不同模态——人类步态下的快乐、悲伤和恐惧。用户对MEI机器人说话、手势和行走的评价表明,仅以语音训练模型为基础,它就能可靠地表达多模态的快乐和悲伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The MEI Robot: Towards Using Motherese to Develop Multimodal Emotional Intelligence
We introduce the first steps in a developmental robot called MEI (multimodal emotional intelligence), a robot that can understand and express emotions in voice, gesture and gait using a controller trained only on voice. Whereas it is known that humans can perceive affect in voice, movement, music and even as little as point light displays, it is not clear how humans develop this skill. Is it innate? If not, how does this emotional intelligence develop in infants? The MEI robot develops these skills through vocal input and perceptual mapping of vocal features to other modalities. We base MEI's development on the idea that motherese is used as a way to associate dynamic vocal contours to facial emotion from an early age. MEI uses these dynamic contours to both understand and express multimodal emotions using a unified model called SIRE (Speed, Intensity, irRegularity, and Extent). Offline experiments with MEI support its cross-modal generalization ability: a model trained with voice data can recognize happiness, sadness, and fear in a completely different modality-human gait. User evaluations of the MEI robot speaking, gesturing and walking show that it can reliably express multimodal happiness and sadness using only the voice-trained model as a basis.
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来源期刊
IEEE Transactions on Autonomous Mental Development
IEEE Transactions on Autonomous Mental Development COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ROBOTICS
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