MAPTRAITS: MACHINE ANALYSIS OF PERSONALITY TRAITS IN HUMAN VIRTUAL AGENT INTERACTIONS

MAPTRAITS：人类虚拟代理交互中人格特质的机器分析

• 批准号: EP/K017500/1
• 负责人: Hatice Gunes
• 金额: $ 12.54万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FK017500%2F1
• 关键词: MAPTRAITS; MACHINE; ANALYSIS; PERSONALITY; TRAITS

Research findings suggest that personality traits such as extraversion, agreeableness, and openness to experience, are tightly coupled with human abilities and behaviour encountered in daily lives: emotional expression, linguistic production, success in interpersonal tasks, leadership ability, general job performance, teacher effectiveness, academic ability, as well as interaction with technology. In fact, human users tend to anthropomorphise computers and virtual agents, treating them as social beings, and interpreting their behaviour similarly to daily human-human interactions.The problem of assessing people's personality is very important for multiple research and business domains such as computer-mediated staff assessment and training, human-computer and human-robot interaction. Despite a growing interest and emphasis on personality traits and their effects on human life in general, and recent advances in machine analysis of human behavioural signals (e.g., vocal expressions, and physiological reactions), pioneering efforts focusing on machine analysis of personality traits have started to emerge only recently: (i) there exist a small number of efforts based on unimodal cues such as written texts/ audio/ speech/ static facial features, (ii) despite tentative efforts on multimodal personality trait analysis, the dynamics (duration, speed, etc.) of multiple cues, which have been shown to be important in human judgments of personalities, have mostly been neglected, (iii) although personality analysis research suggests that a trait exists in all people to a greater or lesser degree (i.e. a person can be anywhere on a continuum ranging from introversion to extraversion), none of the proposed efforts have attempted to assess personality traits continuously in time and space (i.e., how a person can be rated along the multiple trait dimensions at a given interaction time and context), and (iv) how machine (automatic) traits analysis can be utilised for personalised, social and adaptive human - virtual agent interaction has not been investigated.Overall, both the common everyday technology (e.g., personal PCs, smart phones) and the more sophisticated systems people use nowadays (e.g., computer games, assistive technologies, embodied virtual agents, etc.) lack the capability of understanding their human users' personality and behaviour, and of providing socially intelligent, adaptive and engaging human - computer interaction.To address these issues and limitations, MAPTRAITS project will bring around a set of audio-visual tools that can analyse and predict human personality traits dynamically from multiple nonverbal cues and channels (i.e., upper body, head, face, voice and their dynamics) in continuous time and trait space. There is no prospect of building a perfect system for automatic analysis of personality traits that can be used in all possible application domains in 12 months' time. Therefore, as a proof-of-concept, the MAPTRAITS technology will be developed for automatic matching of virtual agent and user personalities, to automatically model what type of users would like to engage with what type of virtual agents to the aim of user engagement enhancement. The motivation for choosing this application area lies in its significance: (i) Research has shown that people's attitudes toward machines and conversational agents is based on the perceived personality of the agent, and their own personality, and (ii) humans are social beings, and currently their everyday life revolves around interacting with computers, virtual agents and robots that are getting increasingly popular as companions, coaches, user interfaces to smart homes, or household robots.

研究结果表明，性格特征，如外向性，宜人性和开放性的经验，与人类的能力和日常生活中遇到的行为紧密相连：情感表达，语言生产，人际交往任务的成功，领导能力，一般工作表现，教师的有效性，学术能力，以及与技术的互动。事实上，人类用户往往拟人化的计算机和虚拟代理，把他们作为社会的人，并解释他们的行为类似于日常的人与人之间的互动。评估人的个性的问题是非常重要的多个研究和商业领域，如计算机介导的员工评估和培训，人机和人机交互。尽管人们对人格特质及其对人类生活的影响越来越感兴趣和重视，而且最近在人类行为信号的机器分析方面取得了进展（例如，语音表达和生理反应），专注于人格特质的机器分析的开创性努力最近才开始出现：（i）存在少量基于单峰线索（例如书面文本/音频/语音/静态面部特征）的努力，（ii）尽管对多峰人格特质分析进行了尝试性努力，但动态（持续时间，速度等）仍然存在。多种线索，这已被证明是重要的，在人类判断的个性，大多被忽视，（iii）虽然人格分析研究表明，一个特点存在于所有的人或多或少的程度（即一个人可以在从内向到外向的连续体上的任何地方），所提出的努力都没有试图在时间和空间上连续地评估人格特质（即，如何在给定的交互时间和环境下沿着多个特质维度对人进行沿着评级），以及（iv）如何将机器（自动）特质分析用于个性化的、社交的和自适应的人-虚拟代理交互。总的来说，常见的日常技术（例如，个人PC、智能电话）和人们现在使用的更复杂的系统（例如，计算机游戏、辅助技术、嵌入式虚拟代理等）缺乏理解人类用户的个性和行为的能力，也无法提供具有社会智能、自适应和引人入胜的人机交互。为了解决这些问题和局限性，MAPTRAITS项目将推出一套视听工具，可以从多种非语言线索和渠道（即，上半身、头、脸、声音及其动态）。没有前景可以在12个月的时间内建立一个完美的系统，用于自动分析人格特征，可以用于所有可能的应用领域。因此，作为概念验证，MAPTRAITS技术将被开发用于虚拟代理和用户个性的自动匹配，以自动建模什么类型的用户想要与什么类型的虚拟代理进行交互，从而达到增强用户交互的目的。选择该应用领域的动机在于其重要性：（i）研究表明，人们对机器和对话代理的态度基于代理的感知个性以及他们自己的个性，以及（ii）人类是社会生物，目前他们的日常生活围绕着与计算机的交互，虚拟代理和机器人作为伴侣、教练、智能家居或家用机器人的用户界面。

项目成果

Social signal processing

• DOI: 10.1109/msp.2007.4286569
• 发表时间: 2007-07-01
• 期刊: IEEE SIGNAL PROCESSING MAGAZINE
• 影响因子: 14.9
• 作者: Pentland, Alex (Sandy)

Automatic analysis of facial attractiveness from video

• DOI: 10.1109/icip.2014.7025851
• 发表时间: 2014-10
• 期刊: 2014 IEEE International Conference on Image Processing (ICIP)
• 作者: Sacide Kalayci;H. K. Ekenel;H. Gunes

Proceedings of the 2014 Mapping Personality Traits Challenge and Workshop

2014 年绘制人格特质挑战赛和研讨会论文集

• 发表时间: 2014
• 作者: Gunes, H

Continuous Prediction of Perceived Traits and Social Dimensions in Space and Time

时空感知特征和社会维度的连续预测

• 发表时间: 2014
• 作者: Celiktutan O

Automatic Prediction of Impressions in Time and across Varying Context: Personality, Attractiveness and Likeability

• DOI: 10.1109/taffc.2015.2513401
• 发表时间: 2017
• 期刊: IEEE Transactions on Affective Computing
• 影响因子: 11.2
• 作者: Oya Celiktutan;H. Gunes