• Corpus ID: 3766480

Can Conversational Agents Express Big Five Personality Traits through Language ? : Evaluating a Psychologically-Informed Language Generator

@inproceedings{Mairesse2008CanCA,
  title={Can Conversational Agents Express Big Five Personality Traits through Language ? : Evaluating a Psychologically-Informed Language Generator},
  author={François Mairesse and Marilyn A. Walker},
  year={2008}
}
Conversation is an essential component of social behavior, one of the primary means by which humans express intentions, beliefs, emotions, attitudes and personality. Thus a key technical capability for dialogue-based conversational agents for interactive entertainment, therapeutic, or learning applications is the ability to support natural conversational interaction. To do so, natural language processing is often applied to allow users flexibility in what they say to the system, but the system… 
Expressing Personalities of Conversational Agents through Visual and Verbal Feedback
As the uses of conversational agents increase, the affective and social abilities of agents become important with their functional abilities. Agents that lack affective abilities could frustrate
Affective Conversational Agents: The Role of Personality and Emotion in Spoken Interactions
In this chapter, we revisit the main theories of human emotion and personality and their implications for the development of affective conversational agents. We focus on the role that emotion plays
Chatbots Language Design: The Influence of Language Variation on User Experience with Tourist Assistant Chatbots
TLDR
The results show that register characteristics are strong predictors of user’s preferences, which points to the needs of designing chatbots with register-appropriate language to improve acceptance and users’ perceptions of chatbot interactions.
Should my Chatbot be Register-Specific? Designing Appropriate Utterances for Tourism
TLDR
This research draws on sociolinguistic theory to investigate how a chatbot's language choices can adhere to the expected social role the agent performs within a given context; i.e., understand whether chatbots design should account for linguistic register.
It's How You Say It: Identifying Appropriate Register for Chatbot Language Design
TLDR
This paper draws on existing sociolinguistic theory to adapt a technique called register analysis to characterize the linguistic register used by humans in a specific conversational context and drive chatbot language design.
How Should My Chatbot Interact? A Survey on Social Characteristics in Human–Chatbot Interaction Design
TLDR
It is argued that chatbots should be enriched with social characteristics that cohere with users’ expectations, ultimately avoiding frustration and dissatisfaction.
How should my chatbot interact ?
TLDR
It is argued that chatbots should be enriched with social characteristics that are coherent with users’ expectations, ultimately avoiding frustration and dissatisfaction.

References

SHOWING 1-10 OF 114 REFERENCES
A Personality-based Framework for Utterance Generation in Dialogue Applications
TLDR
This work proposes a framework for automatically generating language projecting different personality traits based on the ‘Big Five’ model of personality, and shows that the PERSONAGE generator can produce utterances with recognisable personality for all Big Five traits, according to human judges.
How Rude Are You?: Evaluating Politeness and Affect in Interaction
TLDR
POLLy (Politeness for Language Learning), a system which combines a spoken language generator with an artificial intelligence planner to model Brown and Levinson's theory of politeness in collaborative task-oriented dialogue, is presented, with the ultimate goal of providing a fun and stimulating environment for learning English as a second language.
PERSONAGE: Personality Generation for Dialogue
TLDR
PERSONAGE (PERSONAlity GEnerator), the first highly parametrizable language generator for extraversion, an important aspect of personality, is presented.
Personality-rich believable agents that use language
TLDR
Hap, the behavior-based architecture used by the Oz group to construct non-linguistic believable agents, is extended to support natural language text generation, to tightly integrate text generation with other aspects of the agent, including action, perception, inference and emotion.
Improvising linguistic style: social and affective bases for agent personality
TLDR
It is shown how speech act representations common in AI can provide abstract representations from which computer characters can improvise, and the mechanisms proposed introduce the possibility of socially oriented agents, and meet the requirements that lifelike characters be believable.
Speaking More Like You: Lexical, Acoustic/Prosodic, and Discourse Entrainment in Spoken Dialogue Systems
TLDR
The goal is to understand how the different varieties of entrainment correlate with one another and to determine which types of entainment will be both useful and feasible for Spoken Dialogue Systems.
Linguistic Style Matching in Social Interaction
Three experiments were conducted to determine the psychometric properties of language in dyadic interactions. Using text-analysis, it was possible to assess the degree to which people coordinate
Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents
TLDR
An evaluation of the system in which the use of social language was demonstrated to have a significant effect on users’ perceptions of the agent’s knowledgableness and ability to engage users, and on their trust, credibility, and how well they felt the system knew them are discussed.
Individuality and Alignment in Generated Dialogues
TLDR
CRAG is described, which generates dialogues between pairs of agents, who are linguistically distinguishable, but able to align, and makes use of OPENCCG and an over-generation and ranking approach, guided by a set of language models covering both personality and alignment.
Training a sentence planner for spoken dialogue using boosting
...
...