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Role recognition for meeting participants: an approach based on lexical information and social network analysis

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Alessandro VinciarelliAuthors Info & Claims

MM '08: Proceedings of the 16th ACM international conference on Multimedia

Pages 693 - 696

https://doi.org/10.1145/1459359.1459462

Published: 26 October 2008 Publication History

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Abstract

This paper presents experiments on the automatic recognition of roles in meetings. The proposed approach combines two sources of information: the lexical choices made by people playing different roles on one hand, and the Social Networks describing the interactions between the meeting participants on the other hand. Both sources lead to role recognition results significantly higher than chance when used separately, but the best results are obtained with their combination. Preliminary experiments obtained over a corpus of 138 meeting recordings (over 45 hours of material) show that around 70% of the time is labeled correctly in terms of role.

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Cited By

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Zhou JCharoensukmongkol P(2020)The effect of social media use on customer qualification skills and adaptive selling behaviors of export salespeople in ChinaJournal of Asia Business Studies10.1108/JABS-12-2019-037715:2(278-300)Online publication date: 18-Nov-2020
https://doi.org/10.1108/JABS-12-2019-0377
Yu ZWang ZYu ZWang Z(2020)Group Behavior RecognitionHuman Behavior Analysis: Sensing and Understanding10.1007/978-981-15-2109-6_6(139-218)Online publication date: 1-Mar-2020
https://doi.org/10.1007/978-981-15-2109-6_6
Khan KAttique MSyed ISarwar GIrfan MKhan R(2019)A Unified Framework for Head Pose, Age and Gender Classification through End-to-End Face SegmentationEntropy10.3390/e2107064721:7(647)Online publication date: 30-Jun-2019
https://doi.org/10.3390/e21070647
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Role recognition for meeting participants: an approach based on lexical information and social network analysis
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

MM '08: Proceedings of the 16th ACM international conference on Multimedia

October 2008

1206 pages

ISBN:9781605583037

DOI:10.1145/1459359

General Chairs:
Abdulmotaleb EL Saddik
University of Ottawa
,
Son Vuong
University of British Colombia
,
Program Chairs:
Carsten Griwodz
University of Oslo
,
Alberto Del Bimbo
University degli Studi di Firenze
,
K. Selcuk Candan
Arizona State University
,
Alejandro Jaimes
Telefonica R&D, Madrid, Spain

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 26 October 2008

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MM08: ACM Multimedia Conference 2008

October 26 - 31, 2008

British Columbia, Vancouver, Canada

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Zhou JCharoensukmongkol P(2020)The effect of social media use on customer qualification skills and adaptive selling behaviors of export salespeople in ChinaJournal of Asia Business Studies10.1108/JABS-12-2019-037715:2(278-300)Online publication date: 18-Nov-2020
https://doi.org/10.1108/JABS-12-2019-0377
Yu ZWang ZYu ZWang Z(2020)Group Behavior RecognitionHuman Behavior Analysis: Sensing and Understanding10.1007/978-981-15-2109-6_6(139-218)Online publication date: 1-Mar-2020
https://doi.org/10.1007/978-981-15-2109-6_6
Khan KAttique MSyed ISarwar GIrfan MKhan R(2019)A Unified Framework for Head Pose, Age and Gender Classification through End-to-End Face SegmentationEntropy10.3390/e2107064721:7(647)Online publication date: 30-Jun-2019
https://doi.org/10.3390/e21070647
Chowdhury TMuhuri SChakraborty SChakraborty S(2019)Analysis of Adapted Films and Stories Based on Social NetworkIEEE Transactions on Computational Social Systems10.1109/TCSS.2019.29317216:5(858-869)Online publication date: Oct-2019
https://doi.org/10.1109/TCSS.2019.2931721
Flemotomos NGeorgiou PAtkins DNarayanan S(2019)Role Specific Lattice Rescoring for Speaker Role Recognition from Speech Recognition OutputsICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2019.8683900(7330-7334)Online publication date: May-2019
https://doi.org/10.1109/ICASSP.2019.8683900
Liang YZhou XGuo BYu Z(2018)Activity Recognition Using Ubiquitous SensorsWearable Technologies10.4018/978-1-5225-5484-4.ch011(199-230)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-5484-4.ch011
Flemotomos NChen ZAtkins DNarayanan S(2018)Role Annotated Speech Recognition for Conversational Interactions2018 IEEE Spoken Language Technology Workshop (SLT)10.1109/SLT.2018.8639611(1036-1043)Online publication date: Dec-2018
https://doi.org/10.1109/SLT.2018.8639611
Lv JWu BZhou LWang H(2018)StoryRoleNet: Social Network Construction of Role Relationship in VideoIEEE Access10.1109/ACCESS.2018.28320876(25958-25969)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2832087
Diehl D(2018)Language and interaction: applying sociolinguistics to social network analysisQuality & Quantity10.1007/s11135-018-0787-553:2(757-774)Online publication date: 4-Jul-2018
https://doi.org/10.1007/s11135-018-0787-5
Fang SAchard CDubuisson S(2018)Modeling the synchrony between interacting peopleMultimedia Tools and Applications10.1007/s11042-016-4267-477:1(503-518)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4267-4
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Automatic role recognition in multiparty recordings: using social affiliation networks for feature extraction

Role recognition in multiparty recordings using social affiliation networks and discrete distributions

Automatic role recognition in multiparty recordings using social networks and probabilistic sequential models

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