Model of Multi-turn Dialogue in Emotional Chatbot

The intent recognition and natural language understanding of multi-turn dialogue is key for the commercialization of chatbots. Chatbots are mainly used for the processing of specific tasks, and can introduce products to customers or solve related problems, thus saving human resources. Text sentiment...

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Bibliographic Details
Published in2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI) pp. 1 - 5
Main Authors Kao, Chien-Hao, Chen, Chih-Chieh, Tsai, Yu-Tza
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2019
Subjects
Adaptation models
Chatbot
Decoding
Emotion recognition
Emotional category
Generators
Multi-turn
Seq2Seq
SeqGAN
Task analysis
Training
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Summary:The intent recognition and natural language understanding of multi-turn dialogue is key for the commercialization of chatbots. Chatbots are mainly used for the processing of specific tasks, and can introduce products to customers or solve related problems, thus saving human resources. Text sentiment recognition enables a chatbot to know the user's emotional state and select the best response, which is important in medical care. In this study, we combined the multi-turn dialogue model and sentiment recognition model to develop a chatbot, that is designed for used in daily conversations rather than for specific tasks. Thus, the chatbot has the ability to provide the robot's emotions as feedback while talking with a user. Moreover, it can exhibit different emotional reactions based on the content of the user's conversation.
ISSN:2376-6824
DOI:10.1109/TAAI48200.2019.8959855