An Emotion-controlled Dialog Response Generation Model with Dynamic Vocabulary

TL;DR

This paper introduces an emotion-controlled dialog response generation model that leverages a dynamic vocabulary mechanism to enhance response quality and system speed in real-time online applications.

Contribution

It presents a novel model integrating emotion control with dynamic vocabulary to improve response naturalness and efficiency in dialog systems.

Findings

Enhanced response emotional expressiveness

Improved generation speed with dynamic vocabulary

Experimental validation of model effectiveness

Abstract

In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses. However, for real application in online systems, high QPS (queries per second, an indicator of the flow capacity of on-line systems) is required, and a dynamic vocabulary mechanism has been proved available in improving speed of generative models. In this paper, we proposed an emotion-controlled dialog response generation model based on the dynamic vocabulary mechanism, and the experimental results show the benefit of this model.