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.
@inproceedings{DBLP:conf/mobiquitous/LiuWWSLSDD18,
author = {Hui Liu and
Xin Wang and
Yuheng Wei and
Wei Shao and
Jonathan Liono and
Flora D. Salim and
Bo Deng and
Junzhao Du},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/conf/mobiquitous/LiuWWSLSDD18.bib},
booktitle = {Proceedings of the 15th EAI International Conference on Mobile and
Ubiquitous Systems: Computing, Networking and Services, MobiQuitous
2018, 5-7 November 2018, New York City, NY, USA},
doi = {10.1145/3286978.3286995},
editor = {Henning Schulzrinne and
Pan Li},
pages = {392--401},
publisher = {ACM},
timestamp = {Thu, 31 Oct 2019 00:00:00 +0100},
title = {ProMETheus: An Intelligent Mobile Voice Meeting Minutes System},
url = {https://doi.org/10.1145/3286978.3286995},
year = {2018}
}
© 2021 Flora Salim - CRUISE Research Group.