Domain Aware Neural Dialog System

TL;DR

This paper introduces DOM-Seq2Seq, a domain-aware neural dialog system that effectively generates contextually relevant responses across multiple conversation topics by integrating domain classification with sequence-to-sequence modeling.

Contribution

The paper presents a novel domain-aware neural network model combining domain classification with sequence-to-sequence architecture for multi-domain dialog generation.

Findings

DOM-Seq2Seq outperforms standard Seq2Seq models on automatic metrics.

The model effectively captures domain context for relevant response generation.

Demonstrates improved multi-domain conversation handling.

Abstract

We investigate the task of building a domain aware chat system which generates intelligent responses in a conversation comprising of different domains. The domain, in this case, is the topic or theme of the conversation. To achieve this, we present DOM-Seq2Seq, a domain aware neural network model based on the novel technique of using domain-targeted sequence-to-sequence models (Sutskever et al., 2014) and a domain classifier. The model captures features from current utterance and domains of the previous utterances to facilitate the formation of relevant responses. We evaluate our model on automatic metrics and compare our performance with the Seq2Seq model.