Effects of Language Variety on Personality Perception in Embodied Conversational Agents

Krenn, Brigitte; Endraß, Birgit; Kistler, Felix; André, Elisabeth

doi:10.1007/978-3-319-07230-2_41

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…Even for workrelated chatbots, some people still preferred chatbots that were human-like [56], and Liao et al [57] envisioned that a reusable conversational module including common chit-chats and social attributes could be developed. In other words, future chatbot platforms should allow developers to easily build personalized chatbots with different personalities [93] and conversation styles [12,45]. Lastly, developers should aim to improve chatbots' ability to maintain contexts to support smoother and natural conversations [5].…”

Section: Design Considerations For Chatbotsmentioning

confidence: 99%

Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data

Wei¹,

Kim²,

Jung³

et al. 2023

Preprint

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Large Language Model How's your day so far? Prefix 📄 Information format 🤖 Persona modifier A Ongoing Dialogue History Insert as prompt Generate chatbot response B Work & Productivity ✅ Work done ✅ Rate productivity ✅ Other concerns at work ✅ What went well a C Going splendid so far. How is yours? I'm doing well, thanks for asking. Let's talk about your work and productivity yesterday. What work did you get done?Figure 1: An overview of our chatbot running on a large language model through zero-shot response generation, with only a prefix A○ consisting of persona modifier and information format and the ongoing dialogue history B ○. The example conversation is carried on about work a ○. GPT-3 was used for an underlying large language model C ○. Refer to the online demo at https://naver-ai.github.io/llm-chatbot.

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Section: Design Considerations For Chatbotsmentioning

confidence: 99%

Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data

Wei¹,

Kim²,

Jung³

et al. 2023

Preprint

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“…Moreover, our personality model indicates the presence of 7 dimensions, which in our opinion ensures comprehensiveness by following a systematic approach. Previous works as in [24] examined only specific personality aspects, such as introversionextroversion in non-English languages (German and Austrian).…”

Section: A Rq1: How Can We Systematically Develop Ca Personality In T...mentioning

confidence: 99%

“…Likewise, in the CA context [23] proposed a taxonomy of social cues from a multidisciplinary perspective, and they concluded that verbal aspect of the CAs is an important determinant of the social cues. Similarly, researchers in [24] provided clear evidence that synthesized language variety (German and Austrian language) influence human perception about a conversational agent's extroversion. The problem is that the very few works, that have attempted to develop CA personalities, have done so considering English as the medium of human-CA interaction.…”

Section: Introductionmentioning

confidence: 96%

Personality Perceptions of Conversational Agents: A Task-Based Analysis Using Thai as the Conversational Language

Soonpipatskul,

Pal,

Watanapa

et al. 2023

IEEE Access

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Recently there has been a tremendous growth in the popularity of artificial intelligence (AI) based conversational agents (CA). Their support for anthropomorphism and human-likeness makes them popular. However, being anthropomorphic raises a question -do these agents have a personality? Moreover, what effect may personality have on the different tasks these agents perform? Through this research, we aim to answer these two questions by focusing on Thai as the communication modality between the users and the CAs. We use a multi-model approach involving human, brand, and website personality frameworks for proposing our CA personality model. We use a series of steps right from creating the initial pool of personality traits to the final set of personality traits through a systematic approach. Our proposed personality model has 7 dimensions across the two-dimensional continuum (calm -neuroticism, maturity -juvenility, intelligence -ineptness, openness -reserved, sociability -seclusion, self-control -instability, and aestheticsunaesthetics). For examining the effect of personality type on the nature of tasks, we identified two primary task categories (social and functional) and used a multi-criteria decision-making approach to examine the corresponding impacts. Social tasks are impacted most from the (maturity -juvenility) dimension, whereas functional tasks are mostly impacted from the (intelligence -ineptness) dimension. Based on the results we provide suitable recommendations for future research.

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“…Building on this study we investigated how an embodied IVA is perceived when speaking with different regional language varieties (Krenn et al, 2014). The comparison showed that the IVA was rated as more extroverted when speaking with a synthetically generated Viennese or standard Austrian dialect when compared to speaking with the German standard variety.…”

Section: Regional Accentmentioning

confidence: 99%

The impact of mixed-cultural speech on the stereotypical perception of a virtual robot

Obremski

Friedrich²,

Haak³

et al. 2022

Front. Robot. AI

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Despite the fact that mixed-cultural backgrounds become of increasing importance in our daily life, the representation of multiple cultural backgrounds in one entity is still rare in socially interactive agents (SIAs). This paper’s contribution is twofold. First, it provides a survey of research on mixed-cultured SIAs. Second, it presents a study investigating how mixed-cultural speech (in this case, non-native accent) influences how a virtual robot is perceived in terms of personality, warmth, competence and credibility. Participants with English or German respectively as their first language watched a video of a virtual robot speaking in either standard English or German-accented English. It was expected that the German-accented speech would be rated more positively by native German participants as well as elicit the German stereotypes credibility and conscientiousness for both German and English participants. Contrary to the expectations, German participants rated the virtual robot lower in terms of competence and credibility when it spoke with a German accent, whereas English participants perceived the virtual robot with a German accent as more credible compared to the version without an accent. Both the native English and native German listeners classified the virtual robot with a German accent as significantly more neurotic than the virtual robot speaking standard English. This work shows that by solely implementing a non-native accent in a virtual robot, stereotypes are partly transferred. It also shows that the implementation of a non-native accent leads to differences in the perception of the virtual robot.

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Effects of Language Variety on Personality Perception in Embodied Conversational Agents

Cited by 10 publications

References 10 publications

Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data

Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data

Personality Perceptions of Conversational Agents: A Task-Based Analysis Using Thai as the Conversational Language

The impact of mixed-cultural speech on the stereotypical perception of a virtual robot

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