Evaluating multimodal emotion recognition in proactive conversational agents: A user study
This article discusses a study on multimodal emotion recognition in proactive conversational agents. The research highlights the discrepancies between users' facial expressions and their actual emotional states during interactions with the AI. It emphasizes the importance of refining these agents to better adapt to users' emotional changes through linguistic context.
- ▪The study involved 20 users engaging in unscripted dialogues with a conversational agent.
- ▪Users displayed serious facial expressions even when feeling positive emotions, indicating a 'poker face' effect.
- ▪The linguistic analysis of user interactions was found to be more reliable than visual cues in assessing emotions.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.20200 |
| Publication time | Fri, 22 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-22T04:02:00.009Z |
| Last seen | 2026-05-22T04:02:00.009Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | Hr7X_JS84BW2 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Human-Computer Interaction arXiv:2605.20200 (cs) [Submitted on 6 Apr 2026] Title:Evaluating multimodal emotion recognition in proactive conversational agents: A user study Authors:Adnana Dragut, Raquel Lacuesta, F. Xavier Gaya-Morey, Jose M. Buades-Rubio View a PDF of the paper titled Evaluating multimodal emotion recognition in proactive conversational agents: A user study, by Adnana Dragut and 3 other authors View PDF HTML (experimental) Abstract:This article presents a multimodal emotion recognition module integrated into a proactive Socially Interactive Agent (SIA) powered by generative artificial intelligence.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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