Building Culturally-Valid Dynamic Facial Expressions for a Conversational Virtual Agent Using Human Perception
Building Culturally-Valid Dynamic Facial Expressions for a Conversational Virtual Agent Using Human Perception
复制标题
使用人类感知为会话虚拟代理构建文化上有效的动态面部表情
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Rachael E. Jack
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作者：
Chaona Chen;Oliver G. B. Garrod;Robin A. A. Ince;Mary Ellen Foster;P. Schyns;Rachael E. Jack
面部表情用于促进日常互动，包括对话，在每一种文化中。然而，很少有人知道哪些特定的面部表情传达会话信息，这限制了会话虚拟代理的社会信号能力。我们通过直接从文化感知中建模关键会话信息的面部表情，并将其转移到会话虚拟代理来解决这一关键的知识差距。使用一种新颖的基于数据驱动的心理学方法，我们直接从两种不同文化（西欧，东亚）的40名参与者的文化感知中模拟了“思考”，“感兴趣”，“无聊”和“困惑”的面部表情。然后，我们将这些面部表情模型转移到一个流行的会话虚拟代理，并与一组新的文化参与者进行验证。结果表明，在这两种文化中，我们的大多数文化衍生的会话面部表情模型成功地转移到代理。对会话面部表情的进一步跨文化分析显示出系统的相似性（例如，在“感兴趣”中扬起眉毛）和差异（例如，西方人用水平张口，东亚人用垂直张口来表示困惑），这可能促进或阻碍跨文化交流。我们的研究结果表明，使用文化敏感的感知为基础的心理方法来开发心理上有影响力的面部表情会话虚拟代理的力量。我们预计，我们的面部表情模型将增强虚拟代理的社交信号能力及其全球市场。
Facial expressions are used to facilitate daily interactions including conversations, in every culture. However, little is known about which specific facial expressions convey conversational messages, which limits the social signalling capabilities of conversational virtual agents. We address this critical knowledge gap by modeling the facial expressions of key conversational messages directly from cultural perception, and transferring them to a conversational virtual agent. Using a novel data-driven psychology-based method, we modelled facial expressions of 'thinking,' 'interested,' 'bored' and 'confused' directly from the cultural perception of 40 participants across two distinct cultures (Western European, East Asian). We then transferred these facial expression models to a popular conversational virtual agent and validated them with a new group of cultural participants. Results showed that, in both cultures, the majority of our culturally derived conversational facial expression models successfully transferred to the agent. A further cross-cultural analysis of the conversational facial expressions showed systematic similarities (e.g., eye brow raising in 'interested') and differences (e.g., Westerners use horizontal mouth stretch and East Asians use vertical mouth opening to show confusion) that could facilitate or hinder cross-cultural communication. Our results demonstrate the power of using a culturally sensitive perception-based psychological approach to develop psychologically impactful facial expressions for conversational virtual agents. We anticipate that our facial expression models will enhance virtual agent social signalling capabilities and their global marketability.