mlsanityData to 7 Oct 2026

Computational Charisma -- A Brick by Brick Blueprint for Building Charismatic Artificial Intelligence

arXiv 2301.00142 ↗First posted 31 Dec 2022cs.HC cs.AI cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Charisma is considered as one's ability to attract and potentially also influence others. Clearly, there can be considerable interest from an artificial intelligence's (AI) perspective to provide it with such skill. Beyond, a plethora of use cases opens up for computational measurement of human charisma, such as for tutoring humans in the acquisition of charisma, mediating human-to-human conversation, or identifying charismatic individuals in big social data. A number of models exist that base charisma on various dimensions, often following the idea that charisma is given if someone could and would help others. Examples include influence (could help) and affability (would help) in scientific studies or power (could help), presence, and warmth (both would help) as a popular concept. Modelling high levels in these dimensions for humanoid robots or virtual agents, seems accomplishable. Beyond, also automatic measurement appears quite feasible with the recent advances in the related fields of Affective Computing and Social Signal Processing. Here, we, thereforem present a blueprint for building machines that can appear charismatic, but also analyse the charisma of others. To this end, we first provide the psychological perspective including different models of charisma and behavioural cues of it. We then switch to conversational charisma in spoken language as an exemplary modality that is essential for human-human and human-computer conversations. The computational perspective then deals with the recognition and generation of charismatic behaviour by AI. This includes an overview of the state of play in the field and the aforementioned blueprint. We then name exemplary use cases of computational charismatic skills before switching to ethical aspects and concluding this overview and perspective on building charisma-enabled AI.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 23 of its 178 references that are in the map. First posted on arXiv 31 Dec 2022.

Builds on

23 of 178 references.

References · 23

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  2. 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 611
  3. 2019Emergent Tool Use From Multi-Agent Autocurriculacited by 308
  4. 2018Deep Facial Expression Recognition: A Surveycited by 269
  5. 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
  6. 2020Suppressing Uncertainties for Large-Scale Facial Expression Recognitioncited by 157
  7. 2016Eye Tracking for Everyonecited by 155
  8. 2022ZeroEGGS: Zero-shot Example-based Gesture Generation from Speechcited by 83
  9. 2018Learning latent representations for style control and transfer in end-to-end speech synthesiscited by 61
  10. 2019Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Networkcited by 37
  11. 2019Hierarchical Reinforcement Learning for Open-Domain Dialogcited by 27
  12. 2017Agent-Agnostic Human-in-the-Loop Reinforcement Learningcited by 23
11 more
  1. 2021Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Modelcited by 23
  2. 2022The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stresscited by 23
  3. 2021Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysiscited by 22
  4. 2021Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminabilitycited by 19
  5. 2021A Survey on Deep Reinforcement Learning for Audio-Based Applicationscited by 17
  6. 2018Conditioning Deep Generative Raw Audio Models for Structured Automatic Musiccited by 10
  7. 2020Listening to Sounds of Silence for Speech Denoisingcited by 9
  8. 2019Emotionally-Aware Chatbots: A Surveycited by 8
  9. 2019Applying Visual Domain Style Transfer and Texture Synthesis Techniques to Audio - Insights and Challengescited by 1
  10. 2022METEOR Guided Divergence for Video Captioningcited by 1
  11. 2022Automatic Emotion Modelling in Written Storiescited by 1

Built on by

Not cited yet.