The SPPD System for Schema Guided Dialogue State Tracking Challenge
This work addresses scalable multi-domain dialogue state tracking for real-world dialogue systems, representing an incremental advancement in the field.
The authors tackled the Schema Guided dialogue state tracking challenge by proposing a zero-shot dialogue state tracking system using BERT-based NLU models to capture semantic relations between service schema descriptions and dialogue utterances. Their system achieved significant improvement over the baseline.
This paper introduces one of our group's work on the Dialog System Technology Challenges 8 (DSTC8), the SPPD system for Schema Guided dialogue state tracking challenge. This challenge, named as Track 4 in DSTC8, provides a brand new and challenging dataset for developing scalable multi-domain dialogue state tracking algorithms for real world dialogue systems. We propose a zero-shot dialogue state tracking system for this task. The key components of the system is a number of BERT based zero-shot NLU models that can effectively capture semantic relations between natural language descriptions of services' schemas and utterances from dialogue turns. We also propose some strategies to make the system better to exploit information from longer dialogue history and to overcome the slot carryover problem for multi-domain dialogues. The experimental results show that the proposed system achieves a significant improvement compared with the baseline system.