Papers by James Spann
Hitting your MARQ: Multimodal ARgument Quality Assessment in Long Debate Video (2021.emnlp-main)
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| Challenge: | Current literature mostly considers textual content while assessing argument quality, and it is limited to datasets containing short text sequences (18-48 words). |
| Approach: | They propose a set of interpretable debate centric features that are inspired by theories of argument quality and propose MARQ model that summarizes the multimodal signals on long debate videos. |
| Outcome: | The proposed model outperforms baseline models with an error rate reduction of 22.7% on the argument quality prediction task and achieves 81.91% accuracy. |