An Emotion Recognition Conversation System Based on Knowledge Database Automatic Architecture

Abstract

As conversation system it must converse with various users and have to talk about various conversations, so we have to prepare large numbers of information for conversation knowledge database, but it is so especially difficult for us. The wealth of information on the web is full and quick so those make it an attractive resource for seeking quick information to simple. Recognizing a human’s emotional state can be helpful in various contexts. The most promising one is probably the man-machine interaction, the communication between an assisting robot in the household and its human user. In this paper we present an experiment named an emotion recognition conversation system based on knowledge database automatic architecture. In this exploration there are two parts different than the generic conversation system. First, our conversation system can automatic construct of knowledge database base on the Really Simple Syndication parse. Second, this system can recognize emotion from the conversation contents. The experiment showed that this method could achieve better results in practice.