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

Published: 20 October 2008 Publication History

Abstract

This paper presents an approach for the recognition of roles in multiparty recordings. The approach includes two major stages: extraction of Social Affiliation Networks (speaker diarization and representation of people in terms of their social interactions), and role recognition (application of discrete probability distributions to map people into roles). The experiments are performed over several corpora, including broadcast data and meeting recordings, for a total of roughly 90 hours of material. The results are satisfactory for the broadcast data (around 80 percent of the data time correctly labeled in terms of role), while they still must be improved in the case of the meeting recordings (around 45 percent of the data time correctly labeled). In both cases, the approach outperforms significantly chance.

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

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    cover image ACM Conferences
    ICMI '08: Proceedings of the 10th international conference on Multimodal interfaces
    October 2008
    322 pages
    ISBN:9781605581989
    DOI:10.1145/1452392
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    Publication History

    Published: 20 October 2008

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    Author Tags

    1. broadcast data
    2. meeting recordings
    3. role recognition
    4. social network analysis
    5. speaker diarization

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    ICMI '08
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    ICMI '08: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERFACES
    October 20 - 22, 2008
    Crete, Chania, Greece

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    Overall Acceptance Rate 453 of 1,080 submissions, 42%

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    Cited By

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    • (2023)Speech-Based Automatic Prediction of Interview TraitsComputer Vision and Image Processing10.1007/978-3-031-31417-9_44(586-596)Online publication date: 7-May-2023
    • (2021)Personality Traits Classification Using Deep Visual Activity-Based Nonverbal Features of Key-Dynamic ImagesIEEE Transactions on Affective Computing10.1109/TAFFC.2019.294461412:4(1084-1099)Online publication date: 1-Oct-2021
    • (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
    • (2019)A Sequential Data Analysis Approach to Detect Emergent Leaders in Small GroupsIEEE Transactions on Multimedia10.1109/TMM.2019.289550521:8(2107-2116)Online publication date: Aug-2019
    • (2018)Investigation of Small Group Social Interactions Using Deep Visual Activity-Based Nonverbal FeaturesProceedings of the 26th ACM international conference on Multimedia10.1145/3240508.3240685(311-319)Online publication date: 15-Oct-2018
    • (2014)Context in Affective Multiparty and Multimodal InteractionProceedings of the 2014 workshop on Understanding and Modeling Multiparty, Multimodal Interactions10.1145/2666242.2666245(3-8)Online publication date: 16-Nov-2014
    • (2014)Active Clustering with Ensembles for Social structure extractionIEEE Winter Conference on Applications of Computer Vision10.1109/WACV.2014.6835999(969-976)Online publication date: Mar-2014
    • (2014)Hire meIEEE Transactions on Multimedia10.1109/TMM.2014.230716916:4(1018-1031)Online publication date: 1-Jun-2014
    • (2013)Modeling Functional Roles Dynamics in Small Group InteractionsIEEE Transactions on Multimedia10.1109/TMM.2012.222503915:1(83-95)Online publication date: Jan-2013
    • (2012)A Nonverbal Behavior Approach to Identify Emergent Leaders in Small GroupsIEEE Transactions on Multimedia10.1109/TMM.2011.218194114:3(816-832)Online publication date: 1-Jun-2012
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