In EDS ansehen

GCE: An Audio-Visual Dataset for Group Cohesion and Emotion Analysis.

Gespeichert in:
Bibliographische Detailangaben
Titel: GCE: An Audio-Visual Dataset for Group Cohesion and Emotion Analysis.
Autoren: Lim, Eunchae, Ho, Ngoc-Huynh, Pant, Sudarshan, Kang, Young-Shin, Jeon, Seong-Eun, Kim, Seungwon, Kim, Soo-Hyung, Yang, Hyung-Jeong
Quelle: Applied Sciences (2076-3417); Aug2024, Vol. 14 Issue 15, p6742, 21p
Schlagwörter: AFFECTIVE forecasting (Psychology), SOCIAL cohesion, PSYCHOLOGY students, GRADUATE students, EMOTIONS, IMAGE fusion
Abstract: We present the Group Cohesion and Emotion (GCE) dataset, which comprises 1029 segmented films sourced from YouTube. These videos encompass a range of interactions, including interviews, meetings, informal discussions, and other similar contexts. In the annotation process, graduate psychology students were tasked with assigning coherence levels, ranging from 1 to 7, and affective states as negative, neutral, or positive for each 30 s film. We introduce a foundational model that utilizes advanced visual and audio embedding techniques to investigate the concepts of group cohesion and group emotion prediction. The application of Multi-Head Attention (MHA) fusion is utilized to enhance the process of cross-representation learning. The scope of our investigation includes both unimodal and multimodal techniques, which provide insights into the prediction of group cohesion and the detection of group emotion. The results emphasize the effectiveness of the GCE dataset in examining the level of group unity and emotional conditions. [ABSTRACT FROM AUTHOR]
Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Datenbank: Complementary Index
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edb&genre=article&issn=20763417&ISBN=&volume=14&issue=15&date=20240801&spage=6742&pages=6742-6762&title=Applied Sciences (2076-3417)&atitle=GCE%3A%20An%20Audio-Visual%20Dataset%20for%20Group%20Cohesion%20and%20Emotion%20Analysis.&aulast=Lim%2C%20Eunchae&id=DOI:10.3390/app14156742
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Lim%20E
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edb
DbLabel: Complementary Index
An: 178949715
RelevancyScore: 993
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 993.272338867188
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: GCE: An Audio-Visual Dataset for Group Cohesion and Emotion Analysis.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Lim%2C+Eunchae%22">Lim, Eunchae</searchLink><br /><searchLink fieldCode="AR" term="%22Ho%2C+Ngoc-Huynh%22">Ho, Ngoc-Huynh</searchLink><br /><searchLink fieldCode="AR" term="%22Pant%2C+Sudarshan%22">Pant, Sudarshan</searchLink><br /><searchLink fieldCode="AR" term="%22Kang%2C+Young-Shin%22">Kang, Young-Shin</searchLink><br /><searchLink fieldCode="AR" term="%22Jeon%2C+Seong-Eun%22">Jeon, Seong-Eun</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Seungwon%22">Kim, Seungwon</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Soo-Hyung%22">Kim, Soo-Hyung</searchLink><br /><searchLink fieldCode="AR" term="%22Yang%2C+Hyung-Jeong%22">Yang, Hyung-Jeong</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: Applied Sciences (2076-3417); Aug2024, Vol. 14 Issue 15, p6742, 21p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22AFFECTIVE+forecasting+%28Psychology%29%22">AFFECTIVE forecasting (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22SOCIAL+cohesion%22">SOCIAL cohesion</searchLink><br /><searchLink fieldCode="DE" term="%22PSYCHOLOGY+students%22">PSYCHOLOGY students</searchLink><br /><searchLink fieldCode="DE" term="%22GRADUATE+students%22">GRADUATE students</searchLink><br /><searchLink fieldCode="DE" term="%22EMOTIONS%22">EMOTIONS</searchLink><br /><searchLink fieldCode="DE" term="%22IMAGE+fusion%22">IMAGE fusion</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We present the Group Cohesion and Emotion (GCE) dataset, which comprises 1029 segmented films sourced from YouTube. These videos encompass a range of interactions, including interviews, meetings, informal discussions, and other similar contexts. In the annotation process, graduate psychology students were tasked with assigning coherence levels, ranging from 1 to 7, and affective states as negative, neutral, or positive for each 30 s film. We introduce a foundational model that utilizes advanced visual and audio embedding techniques to investigate the concepts of group cohesion and group emotion prediction. The application of Multi-Head Attention (MHA) fusion is utilized to enhance the process of cross-representation learning. The scope of our investigation includes both unimodal and multimodal techniques, which provide insights into the prediction of group cohesion and the detection of group emotion. The results emphasize the effectiveness of the GCE dataset in examining the level of group unity and emotional conditions. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=178949715
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/app14156742
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 6742
    Subjects:
      – SubjectFull: AFFECTIVE forecasting (Psychology)
        Type: general
      – SubjectFull: SOCIAL cohesion
        Type: general
      – SubjectFull: PSYCHOLOGY students
        Type: general
      – SubjectFull: GRADUATE students
        Type: general
      – SubjectFull: EMOTIONS
        Type: general
      – SubjectFull: IMAGE fusion
        Type: general
    Titles:
      – TitleFull: GCE: An Audio-Visual Dataset for Group Cohesion and Emotion Analysis.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Lim, Eunchae
      – PersonEntity:
          Name:
            NameFull: Ho, Ngoc-Huynh
      – PersonEntity:
          Name:
            NameFull: Pant, Sudarshan
      – PersonEntity:
          Name:
            NameFull: Kang, Young-Shin
      – PersonEntity:
          Name:
            NameFull: Jeon, Seong-Eun
      – PersonEntity:
          Name:
            NameFull: Kim, Seungwon
      – PersonEntity:
          Name:
            NameFull: Kim, Soo-Hyung
      – PersonEntity:
          Name:
            NameFull: Yang, Hyung-Jeong
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Text: Aug2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 20763417
          Numbering:
            – Type: volume
              Value: 14
            – Type: issue
              Value: 15
          Titles:
            – TitleFull: Applied Sciences (2076-3417)
              Type: main
ResultId 1