论文标题
模式指导对话状态跟踪挑战的SPD系统
The SPPD System for Schema Guided Dialogue State Tracking Challenge
论文作者
论文摘要
本文介绍了我们小组在“对话系统技术”技术挑战8（DSTC8）的工作之一，这是模式指导的对话状态跟踪挑战的SPPD系统。这一挑战被DSTC8中的曲目4命名，提供了一个全新且具有挑战性的数据集，用于开发可扩展的多域对话状态跟踪算法，用于现实世界中对话系统。我们为此任务提出了一个零摄像的对话状态跟踪系统。该系统的关键组成部分是许多基于BERT的零击NLU模型，它们可以有效地捕获服务模式的自然语言描述与对话转弯中的话语之间的语言描述。我们还提出了一些策略，以使系统更好地利用较长的对话历史记录中的信息，并克服多域对话的插槽结转问题。实验结果表明，与基线系统相比，所提出的系统取得了显着改善。
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.
