Author:
Huang Tai-Chia,Hsieh Chia-Hsuan,Wang Hei-Chia
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.
Subject
Library and Information Sciences,Information Systems
Reference35 articles.
1. Banerjee, S. and Rudnicky, A.I. (2006), “A TextTiling-based approach to topic boundary detection in meetings”, paper presented at the Proceedings of the Annual Conference of the International Speech Communication Association, pp. 57-60.
2. Latent Dirichlet allocation;Journal of Machine Learning Research,2003
3. Carbonell, J. and Goldstein, J. (1998), “The use of MMR, diversity-based reranking for reordering documents and producing summaries”, paper presented at the Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Melbourne, August 24-28.
4. Learning routines over long-term sensor data using topic models;Expert Systems,2014
5. Choi, F., Wiemer-Hastings, P. and Moore, J. (2001), “Latent semantic analysis for text segmentation”, paper presented at the Proceedings of the Proceedings of EMNLP, Citeseer.
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