基于特征参数的分层数据库用于机器人各种多模态表达式的生成

W. Kim, J. Park, Won Hyong Lee, M. Chung
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引用次数: 3

摘要

本文提出了一个可靠、多样、可扩展、可用的表达式生成系统。该系统基于分层数据库和机器人的情绪状态、机器人想要说的句子等上下文信息,自动生成同步的多模态表达。与之前的系统相比,基于特征参数的系统更容易根据机器人的情绪生成新的表情和修改表情。在我们的系统中,有句子模块、情感模块和表达模块。我们只关注机器人的表达模块。为了自动生成表情,我们使用句子和情感模块的输出。我们将机器人语句分为13种类型,机器人情感分为3种类型。针对这39个类别和肢体语言,我们构建了包含128种表情的行为数据库。为了可靠性和表情的多样性,我们获得了专业演员的表情数据,并请漫画家根据定义的类别绘制机器人的表情草图。
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Hierarchical database based on feature parameters for various multimodal expression generation of robot
In this paper, we propose reliable, diverse, expansible, and usable expression generation system. Proposed system is to generate synchronized multimodal expression automatically based on hierarchical database and context information such as robot's emotional state and sentence robot is trying to say. Compared to prior system, our system based on feature parameters is much easier to generate new expression and modify expressions according to the robot's emotion. In our system, there are sentence module, emotion module, and expression module. We focus on only robot's expression module. In order to generate expressions automatically, we use outputs of the sentence and emotion modules. We have classified robot sentence under 13 types and robot emotion under 3 types. About all 39 categories and body language, we have constructed behavior database with 128 expressions. For the reliability and the variety of expressions, a professional actor's expression data have been obtained and we requested a cartoonist to draw sketch of robot's expressions corresponding to defined categories.
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