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Dialogue State Tracking Challenge 4 (DSTC4)

The proposed model proposes an end-to-end attentional role-based contextual model that automatically learns speaker-specific contextual encoding and investigates various content-aware and time-aware attention mechanisms on a benchmark multi-domain human-human dialogue dataset.

Data and Resources

Cite this as

Po-Chun Chen, Ta-Chung Chi, Shang-Yu Su, Yun-Nung Chen (2025). Dataset: Dialogue State Tracking Challenge 4 (DSTC4). https://doi.org/10.57702/sthakrow

DOI retrieved: January 2, 2025

Additional Info

Field Value
Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.1710.00165
Author Po-Chun Chen
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Ta-Chung Chi
Shang-Yu Su
Yun-Nung Chen
Homepage https://github.com/MiuLab/Time-SLU