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Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Study

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ChapterMultimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions

Heysem Kaya2018

Chapter2018

Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions

Heysem Kaya · Albert Ali Salah

16 citations·0/0 files stored·The Springer series on challenges in machine learning

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AI and HR Technologies Emotion and Mood Recognition Face recognition and analysis

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References

2002A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition.2006Universal dimensions of social cognition: warmth and competence 2013The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism 2017Video-based emotion recognition in the wild using deep transfer learning and score fusion 2016ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results 2016Deep Bimodal Regression for Apparent Personality Analysis 2016Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition 2014Predicting Personality Traits using Multimodal Information

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2020Multimodal analysis of personality traits on videos of self-presentation and induced behaviorarticle · 11 shared references 2021Multimodal assessment of apparent personality using feature attention and error consistency constraintarticle · 10 shared references 2016Multimodal fusion of audio, scene, and face features for first impression estimationother · 9 shared references 2019On the Effect of Observed Subject Biases in Apparent Personality Analysis From Audio-Visual Signalsarticle · 7 shared references 2022Deep Personality Trait Recognition: A Surveyreview · 7 shared references 2019PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationshiparticle · 6 shared references

Details

Year2018

Typechapter

Published2018-01-01

VenueThe Springer series on challenges in machine learning

ISSN-L2520-131X

Languageen

Citations16

Files0 public / 0

ShelfAI and HR Technologies

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doi10.1007/978-3-319-98131-4_10

openalex_workW2902018318

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