ProMETheus: An Intelligent Mobile Voice Meeting Minutes System

Liu, H, Wang, X, Wei, Y, Shao, W, Liono, J, Salim, F, Bo, D and Du, J 2018, 'ProMETheus: An Intelligent Mobile Voice Meeting Minutes System', in Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, New York, NY, USA, 5-7 November 2018, pp. 392-401.


Document type: Conference Paper
Collection: Conference Papers

Title ProMETheus: An Intelligent Mobile Voice Meeting Minutes System
Author(s) Liu, H
Wang, X
Wei, Y
Shao, W
Liono, J
Salim, F
Bo, D
Du, J
Year 2018
Conference name MobiQuitous 2018 - 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
Conference location New York, NY, USA
Conference dates 5-7 November 2018
Proceedings title Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
Publisher ACM
Place of publication United States
Start page 392
End page 401
Total pages 10
Abstract In this paper, we focus on designing and developing ProMETheus, an intelligent system for meeting minutes generated from audio data. The first task in ProMETheus is to recognize the speakers from noisy audio data. Speaker recognition algorithm is used to automatically identify who is speaking according to the speech in an audio data. Naturally, speech recognition will transcribe speakers' audio to text so that ProMETheus can generate the complete meeting text with speakers' name chronologically. In order to show the subject of the meeting and the agreed action, we use text summarization algorithm that can extract meaningful key phrases and summary sentences from the complete meeting text. In addition, sentiment analysis for meeting text of different speakers can make the agreed action more humane due to calculating the relevance score of each course by the sentiment and attitude in text tone. The ProMETheus is capable of accurately summarizing the meeting and analyzing the agreed action. Our robust system is evaluated on a real-world audio meeting dataset that involves multiple speakers in each meeting session.
Subjects Ubiquitous Computing
Computer-Human Interaction
Computer System Architecture
Keyword(s) meeting minutes
meeting text
sentiment analysis
speaker recognition
speech recognition
text summarization
DOI - identifier 10.1145/3286978.3286995
Copyright notice © 2018 ACM
ISBN 9781450360937
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