Schema Encoding for Transferable Dialogue State Tracking
Dialogue state tracking (DST) is an essential sub-task for task-oriented dialogue systems. Recent work has focused on deep neural models for DST. However, the neural models require a large dataset for training. Furthermore, applying them to another domain needs a new dataset because the neural models are generally trained to imitate the given dataset. In this paper, we propose Schema Encoding for Transferable Dialogue State Tracking (SETDST), which is a neural DST method for effective transfer to new domains. Transferable DST could assist developments of dialogue systems even with few dataset on target domains. We use a schema encoder not just to imitate the dataset but to comprehend the schema of the dataset. We aim to transfer the model to new domains by encoding new schemas and using them for DST on multi-domain settings. As a result, SET-DST improved the joint accuracy by 1.46 points on MultiWOZ 2.1.
Code (0)
등록된 구현이 없습니다.
Tasks
Dialogue State TrackingTask-Oriented Dialogue SystemsMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Schema Encoding for Transferable Dialogue State Tracking
Dialogue state tracking (DST) is an essential sub-task for task-oriented dialogue systems.Recent work has focused on deep neural models for DST.However, the neural models require a large dataset for training.Furthermore,…
Dialogue State TrackingDialogue State Tracking with a Language Model using Schema-Driven Prompting
Task-oriented conversational systems often use dialogue state tracking to represent the user's intentions, which involves filling in values of pre-defined slots. Many approaches have been proposed, often using task-speci…
Dialogue State TrackingLanguage ModelingLanguage ModellingMulti-domain Dialogue State TrackingA Multi-Task BERT Model for Schema-Guided Dialogue State Tracking
Task-oriented dialogue systems often employ a Dialogue State Tracker (DST) to successfully complete conversations. Recent state-of-the-art DST implementations rely on schemata of diverse services to improve model robustn…
Dialogue State TrackingIntent Classificationslot-fillingSlot Filling+3Schema Graph-Guided Prompt for Multi-Domain Dialogue State Tracking
Tracking dialogue states is an essential topic in task-oriented dialogue systems, which involve filling in the necessary information in pre-defined slots corresponding to a schema. While general pre-trained language mode…
Dialogue State TrackingGraph Neural NetworkLanguage ModelingLanguage Modelling+4The SPPD System for Schema Guided Dialogue State Tracking Challenge
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…
Dialogue State TrackingMulti-domain Dialogue State Tracking