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

arXiv: https://arxiv.org/abs/2301.00142 · HTML: https://mlsanity.com/paper/2301.00142/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 178 references that are in the map.
- First posted on arXiv 31 Dec 2022.

## Builds on (most cited first, 23 of 23)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [AudioLM: a Language Modeling Approach to Audio Generation](https://mlsanity.com/paper/2209.03143/) (2022)
- [Emergent Tool Use From Multi-Agent Autocurricula](https://mlsanity.com/paper/1909.07528/) (2019)
- [Deep Facial Expression Recognition: A Survey](https://mlsanity.com/paper/1804.08348/) (2018)
- [A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://mlsanity.com/paper/2009.08441/) (2020)
- [Suppressing Uncertainties for Large-Scale Facial Expression Recognition](https://mlsanity.com/paper/2002.10392/) (2020)
- [Eye Tracking for Everyone](https://mlsanity.com/paper/1606.05814/) (2016)
- [ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech](https://mlsanity.com/paper/2209.07556/) (2022)
- [Learning latent representations for style control and transfer in end-to-end speech synthesis](https://mlsanity.com/paper/1812.04342/) (2018)
- [Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network](https://mlsanity.com/paper/1902.01019/) (2019)
- [Hierarchical Reinforcement Learning for Open-Domain Dialog](https://mlsanity.com/paper/1909.07547/) (2019)
- [Agent-Agnostic Human-in-the-Loop Reinforcement Learning](https://mlsanity.com/paper/1701.04079/) (2017)
- [Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model](https://mlsanity.com/paper/2106.02596/) (2021)
- [The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress](https://mlsanity.com/paper/2207.05691/) (2022)
- [Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis](https://mlsanity.com/paper/2109.08256/) (2021)
- [Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability](https://mlsanity.com/paper/2104.01408/) (2021)
- [A Survey on Deep Reinforcement Learning for Audio-Based Applications](https://mlsanity.com/paper/2101.00240/) (2021)
- [Conditioning Deep Generative Raw Audio Models for Structured Automatic Music](https://mlsanity.com/paper/1806.09905/) (2018)
- [Listening to Sounds of Silence for Speech Denoising](https://mlsanity.com/paper/2010.12013/) (2020)
- [Emotionally-Aware Chatbots: A Survey](https://mlsanity.com/paper/1906.09774/) (2019)
- [Applying Visual Domain Style Transfer and Texture Synthesis Techniques to Audio - Insights and Challenges](https://mlsanity.com/paper/1901.10240/) (2019)
- [METEOR Guided Divergence for Video Captioning](https://mlsanity.com/paper/2212.10690/) (2022)
- [Automatic Emotion Modelling in Written Stories](https://mlsanity.com/paper/2212.11382/) (2022)

## 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.