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arXiv · 2101.07339

MONAH: Multi-Modal Narratives for Humans to analyze conversations

Joshua Y. Kim·Greyson Y. Kim·Chunfeng Liu·Rafael A. Calvo·Silas C. R. Taylor·Kalina Yacef
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Abstract

In conversational analyses, humans manually weave multimodal information into the transcripts, which is significantly time-consuming. We introduce a system that automatically expands the verbatim transcripts of video-recorded conversations using multimodal data streams. This system uses a set of preprocessing rules to weave multimodal annotations into the verbatim transcripts and promote interpretability. Our feature engineering contributions are two-fold: firstly, we identify the range of multimodal features relevant to detect rapport-building; secondly, we expand the range of multimodal annotations and show that the expansion leads to statistically significant improvements in detecting rapport-building.

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Joshua Y. Kim, Greyson Y. Kim, Chunfeng Liu, Rafael A. Calvo, Silas C. R. Taylor, Kalina Yacef. 2021-01-18. MONAH: Multi-Modal Narratives for Humans to analyze conversations. https://arxiv.org/abs/2101.07339

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