TY - GEN
T1 - Research and Design of a Chinese Chatbot with Emotion
AU - Zhou, Yan
AU - Dai, Zixi
AU - Wang, Qingjuan
AU - Ren, Lingling
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In recent years, there has been a growing use of intelligent chatbots in various scenarios. However, most of the current chatbots are limited to simple and mechanical interactions. To address this, by analyzing the formation principle of human emotion, an intelligent chatbot with emotion is studied and designed in this paper. Firstly, open data sets are collected, word segmentation is processed on them, and the feature vectors are extracted by word embedding technology. Then, different neural networks are designed and optimized for two algorithm modules: analyzing emotional tendency of input text, and generating reply text. Finally, the chatbot is achieved. The experimental results show that the accuracy rate, recall rate and F1 score of the algorithm of emotional tendency analyzing are all around 90%, and the reply text quality generated by the chatbot is also relatively ideal.
AB - In recent years, there has been a growing use of intelligent chatbots in various scenarios. However, most of the current chatbots are limited to simple and mechanical interactions. To address this, by analyzing the formation principle of human emotion, an intelligent chatbot with emotion is studied and designed in this paper. Firstly, open data sets are collected, word segmentation is processed on them, and the feature vectors are extracted by word embedding technology. Then, different neural networks are designed and optimized for two algorithm modules: analyzing emotional tendency of input text, and generating reply text. Finally, the chatbot is achieved. The experimental results show that the accuracy rate, recall rate and F1 score of the algorithm of emotional tendency analyzing are all around 90%, and the reply text quality generated by the chatbot is also relatively ideal.
KW - BI-LSTM Neural Network
KW - Chatbot
KW - Sentiment Analysis
KW - Sequence-to-Sequence
KW - Word Embedding
UR - http://www.scopus.com/inward/record.url?scp=85182022668&partnerID=8YFLogxK
U2 - 10.1109/PRML59573.2023.10348274
DO - 10.1109/PRML59573.2023.10348274
M3 - Conference contribution
AN - SCOPUS:85182022668
T3 - 2023 IEEE 4th International Conference on Pattern Recognition and Machine Learning, PRML 2023
SP - 470
EP - 474
BT - 2023 IEEE 4th International Conference on Pattern Recognition and Machine Learning, PRML 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2023
Y2 - 4 August 2023 through 6 August 2023
ER -
