About

Dialogue state tacking consists of determining at each turn of a dialogue the full representation of what the user wants at that point in the dialogue, which contains a goal constraint, a set of requested slots, and the user's dialogue act.

Benchmarks

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Datasets

Greatest papers with code

CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

TACL 2020 fighting41love/funNLP

To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.

DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS

A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset

27 Aug 2020NVIDIA/NeMo

Dialog State Tracking (DST) is one of the most crucial modules for goal-oriented dialogue systems.

DATA AUGMENTATION DIALOGUE STATE TRACKING GOAL-ORIENTED DIALOGUE SYSTEMS

MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems

EMNLP 2020 budzianowski/multiwoz

In this paper, we propose Minimalist Transfer Learning (MinTL) to simplify the system design process of task-oriented dialogue systems and alleviate the over-dependency on annotated data.

DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING

MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselines

WS 2020 budzianowski/multiwoz

We also benchmark a few state of the art dialogue state tracking models on the corrected dataset to facilitate comparison for future work.

DIALOGUE STATE TRACKING

Schema-Guided Dialogue State Tracking Task at DSTC8

2 Feb 2020google-research-datasets/dstc8-schema-guided-dialogue

The goal of this task is to develop dialogue state tracking models suitable for large-scale virtual assistants, with a focus on data-efficient joint modeling across domains and zero-shot generalization to new APIs.

DATA AUGMENTATION DIALOGUE STATE TRACKING

Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems

NAACL 2018 google-research-datasets/simulated-dialogue

To address this challenge, we propose a hybrid imitation and reinforcement learning method, with which a dialogue agent can effectively learn from its interaction with users by learning from human teaching and feedback.

DIALOGUE STATE TRACKING IMITATION LEARNING TASK-ORIENTED DIALOGUE SYSTEMS

Scalable Multi-Domain Dialogue State Tracking

29 Dec 2017google-research-datasets/simulated-dialogue

We introduce a novel framework for state tracking which is independent of the slot value set, and represent the dialogue state as a distribution over a set of values of interest (candidate set) derived from the dialogue history or knowledge.

DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING