Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems (P19-1)
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| Challenge: | Existing work on video-grounded dialogue systems is limited by feature space and semantic information. |
| Approach: | They propose multimodal transformer networks to encode videos and incorporate information from different modalities. |
| Outcome: | The proposed system generates appropriate conversational response to queries of humans based on visual and audio aspects of a given video . it also generalizes to another multimodal visual-grounded dialogue task, and obtains promising performance. |
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Yuwei Fang, Willi Menapace, Aliaksandr Siarohin, Tsai-Shien Chen, Kuan-Chieh Wang, Ivan Skorokhodov, Graham Neubig, Sergey Tulyakov
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