DeepAI
Log In Sign Up

Discovering Dialog Structure Graph for Open-Domain Dialog Generation

12/31/2020
by   Jun Xu, et al.
0

Learning interpretable dialog structure from human-human dialogs yields basic insights into the structure of conversation, and also provides background knowledge to facilitate dialog generation. In this paper, we conduct unsupervised discovery of dialog structure from chitchat corpora, and then leverage it to facilitate dialog generation in downstream systems. To this end, we present a Discrete Variational Auto-Encoder with Graph Neural Network (DVAE-GNN), to discover a unified human-readable dialog structure. The structure is a two-layer directed graph that contains session-level semantics in the upper-layer vertices, utterance-level semantics in the lower-layer vertices, and edges among these semantic vertices. In particular, we integrate GNN into DVAE to fine-tune utterance-level semantics for more effective recognition of session-level semantic vertex. Furthermore, to alleviate the difficulty of discovering a large number of utterance-level semantics, we design a coupling mechanism that binds each utterance-level semantic vertex with a distinct phrase to provide prior semantics. Experimental results on two benchmark corpora confirm that DVAE-GNN can discover meaningful dialog structure, and the use of dialog structure graph as background knowledge can facilitate a graph grounded conversational system to conduct coherent multi-turn dialog generation.

READ FULL TEXT

page 8

page 13

04/22/2018

Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation

The encoder-decoder dialog model is one of the most prominent methods us...
05/01/2020

USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation

The lack of meaningful automatic evaluation metrics for dialog has imped...
07/12/2019

Effective Incorporation of Speaker Information in Utterance Encoding in Dialog

In dialog studies, we often encode a dialog using a hierarchical encoder...
09/17/2019

Hierarchical Reinforcement Learning for Open-Domain Dialog

Open-domain dialog generation is a challenging problem; maximum likeliho...
05/30/2019

Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention

Semantically controlled neural response generation on limited-domain has...
06/21/2019

Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems

Building an open-domain conversational agent is a challenging problem. C...
07/13/2021

TSCAN : Dialog Structure discovery using SCAN

Can we discover dialog structure by dividing utterances into labelled cl...