Automatic meeting summarization and topic detection system
Data Technologies and Applications
ISSN: 2514-9288
Article publication date: 27 April 2018
Issue publication date: 20 August 2018
Abstract
Purpose
Producing meeting documents requires an instantaneous recorder during meetings, which costs extra human resources and takes time to amend the file. However, a high-quality meeting document can enable users to recall the meeting content efficiently. The paper aims to discuss these issues.
Design/methodology/approach
An application based on this framework is developed to help the users find topics and obtain summarizations of meeting contents without extra effort. This app uses the Bluemix speech recognizer to obtain speech transcripts. It then combines latent Dirichlet allocation and a TextTiling algorithm with the speech script of meetings to detect boundaries between different topics and evaluate the topics in each segment. TextTeaser, an open API based on a feature-based approach, is then used to summarize the speech transcripts.
Findings
The results indicate that the summaries generated by the machine are 85 percent similar to the records written by humankind.
Originality/value
To reduce the human effort in generating meeting reports, this paper presents a framework to record and analyze meeting contents automatically by voice recognition, topic detection, and extractive summarization.
Keywords
Acknowledgements
The research was based on the work supported by the Taiwan Ministry of Science and Technology under Grant No. MOST 103-2410-H-006-055-MY3.
Citation
Huang, T.-C., Hsieh, C.-H. and Wang, H.-C. (2018), "Automatic meeting summarization and topic detection system", Data Technologies and Applications, Vol. 52 No. 3, pp. 351-365. https://doi.org/10.1108/DTA-09-2017-0062
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited