Summary of Multilingual Dyadic Interaction Corpus Noxi+j: Toward Understanding Asian-european Non-verbal Cultural Characteristics and Their Influences on Engagement, by Marius Funk et al.
Multilingual Dyadic Interaction Corpus NoXi+J: Toward Understanding Asian-European Non-verbal Cultural Characteristics and their Influences on Engagement
by Marius Funk, Shogo Okada, Elisabeth André
First submitted to arxiv on: 9 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The study examines non-verbal behavior in conversations across cultures, aiming to understand its impact on engagement recognition. It expands the NoXi dataset by adding Japanese and Chinese interactions, extracting multimodal features like speech acoustics, facial expressions, backchanneling, and gestures. Statistical analysis identifies culturally dependent and independent features, as well as common ones among languages. Correlation analysis shows a link between cultural differences in input features and the importance of those features for engagement prediction using LSTM models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The study looks at how people behave during conversations and how that affects their emotional state. It takes data from different countries like France, Germany, Japan, China, and the UK, and analyzes it to see what’s similar and what’s different between cultures. The researchers want to know if these differences help or hurt our ability to understand when someone is engaged in a conversation. |
Keywords
» Artificial intelligence » Lstm
