An Interactive Chatbot for University Open Day

Fengyu Liu; Xu Yang; Yapeng Wang

doi:10.1109/ICSESS54813.2022.9930277

An Interactive Chatbot for University Open Day

Fengyu Liu, Xu Yang, Yapeng Wang

Faculty of Applied Sciences

Macao Polytechnic University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022
Editors	Li Wenzheng
Publisher	IEEE Computer Society
Pages	214-217
Number of pages	4
ISBN (Electronic)	9781665410311
DOIs	https://doi.org/10.1109/ICSESS54813.2022.9930277
Publication status	Published - 2022
Event	13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022 - Beijing, China Duration: 21 Oct 2022 → 23 Oct 2022

Publication series

Name	Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Volume	2022-October
ISSN (Print)	2327-0586
ISSN (Electronic)	2327-0594

Conference

Conference	13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022
Country/Territory	China
City	Beijing
Period	21/10/22 → 23/10/22

Keywords

Chatbot
NLP
Neural Network

Access to Document

10.1109/ICSESS54813.2022.9930277

Cite this

Liu, F., Yang, X., & Wang, Y. (2022). An Interactive Chatbot for University Open Day. In L. Wenzheng (Ed.), Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022 (pp. 214-217). (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS; Vol. 2022-October). IEEE Computer Society. https://doi.org/10.1109/ICSESS54813.2022.9930277

Liu, Fengyu ; Yang, Xu ; Wang, Yapeng. / An Interactive Chatbot for University Open Day. Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022. editor / Li Wenzheng. IEEE Computer Society, 2022. pp. 214-217 (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS).

@inproceedings{b8d3eceace124446964a9041bf90b066,

title = "An Interactive Chatbot for University Open Day",

abstract = "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.",

keywords = "Chatbot, NLP, Neural Network",

author = "Fengyu Liu and Xu Yang and Yapeng Wang",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022 ; Conference date: 21-10-2022 Through 23-10-2022",

year = "2022",

doi = "10.1109/ICSESS54813.2022.9930277",

language = "English",

series = "Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS",

publisher = "IEEE Computer Society",

pages = "214--217",

editor = "Li Wenzheng",

booktitle = "Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022",

address = "United States",

}

Liu, F, Yang, X & Wang, Y 2022, An Interactive Chatbot for University Open Day. in L Wenzheng (ed.), Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022. Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS, vol. 2022-October, IEEE Computer Society, pp. 214-217, 13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022, Beijing, China, 21/10/22. https://doi.org/10.1109/ICSESS54813.2022.9930277

An Interactive Chatbot for University Open Day. / Liu, Fengyu; Yang, Xu ; Wang, Yapeng.
Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022. ed. / Li Wenzheng. IEEE Computer Society, 2022. p. 214-217 (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS; Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Interactive Chatbot for University Open Day

AU - Liu, Fengyu

AU - Yang, Xu

AU - Wang, Yapeng

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 - https://www.scopus.com/pages/publications/85141936862

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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 -

Liu F, Yang X , Wang Y. An Interactive Chatbot for University Open Day. In Wenzheng L, editor, Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022. IEEE Computer Society. 2022. p. 214-217. (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS). doi: 10.1109/ICSESS54813.2022.9930277

An Interactive Chatbot for University Open Day

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Keywords

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