TY - GEN
T1 - An Interactive Chatbot for University Open Day
AU - Liu, Fengyu
AU - Yang, Xu
AU - Wang, Yapeng
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Macau Polytechnic University (MPU) welcomes many visitors on its open day, and it is therefore necessary to provide them with excellent service and guidance. However, there are many difficulties in providing information to visitors, such as the occupation of human resources, language barriers and inaccurate answers, etc. By developing a chatbot to answer the questions from visitors instantly and consistently, helps to save human resources and increase the efficiency of work. An intelligent chatbot can not only provide accurate and appropriate responses but also bring a great communication experience to the visitors. This research uses Natural Language Processing (NLP) and Deep Learning (DL) techniques to develop a chatbot that can engage in interactive conversations with visitors for the MPU open day. A high-performance neural network is built to learn from the given dataset and can accurately answer questions about the MPU open day. Besides, STT (Speech-to-Text) and TTS (Text-to-Speech) APIs are used in this work to assist the communication between computers and humans. This work can be used as a reference framework of fast implementation of a chatbot for any knowledge area with an easy-to-adapt web interface.
AB - Macau Polytechnic University (MPU) welcomes many visitors on its open day, and it is therefore necessary to provide them with excellent service and guidance. However, there are many difficulties in providing information to visitors, such as the occupation of human resources, language barriers and inaccurate answers, etc. By developing a chatbot to answer the questions from visitors instantly and consistently, helps to save human resources and increase the efficiency of work. An intelligent chatbot can not only provide accurate and appropriate responses but also bring a great communication experience to the visitors. This research uses Natural Language Processing (NLP) and Deep Learning (DL) techniques to develop a chatbot that can engage in interactive conversations with visitors for the MPU open day. A high-performance neural network is built to learn from the given dataset and can accurately answer questions about the MPU open day. Besides, STT (Speech-to-Text) and TTS (Text-to-Speech) APIs are used in this work to assist the communication between computers and humans. This work can be used as a reference framework of fast implementation of a chatbot for any knowledge area with an easy-to-adapt web interface.
KW - Chatbot
KW - NLP
KW - Neural Network
UR - http://www.scopus.com/inward/record.url?scp=85141936862&partnerID=8YFLogxK
U2 - 10.1109/ICSESS54813.2022.9930277
DO - 10.1109/ICSESS54813.2022.9930277
M3 - Conference contribution
AN - SCOPUS:85141936862
T3 - Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
SP - 214
EP - 217
BT - Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022
A2 - Wenzheng, Li
PB - IEEE Computer Society
T2 - 13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022
Y2 - 21 October 2022 through 23 October 2022
ER -