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Dataset . 2022
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2022
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2022
Data sources: Datacite
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Passau-SFCH

Authors: Christ, Lukas; Amiriparian, Shahin; Kathan, Alexander; Müller, Niklas; König, Andreas; Schuller, Björn W.;
Abstract

The novel Passau-Spontaneous Football Coach Humor (Passau-SFCH) dataset consists of press conference recordings of 10 different German Bundesliga football coaches collected in 2017. The data provided here only includes segments in which the respective coach is speaking, accounting for about 11 hours of data. There are three continuous annotations (2 Hz rate): Humour, as well as sentiment and direction (self- vs. others-directed) as proposed in the Humor Style Questionnaire by [1]. For a detailled description of the data, see [2]. The package includes: raw data segmented videos segmented audios manually corrected transcriptions extracted features, cf. [2] gold standard labels, cf. [2] Note that a variant of this dataset has been featured in the Multimodal Sentiment Analysis Challenge (MuSe) 2022 [3,4]. For questions, please contact Lukas Christ at lukas[dot]christ[at]informatik[dot]uni-augsburg[dot]de. [1] Martin, Rod A., et al. "Individual differences in uses of humor and their relation to psychological well-being: Development of the Humor Styles Questionnaire." Journal of research in personality 37.1 (2003): 48-75. [2] L. Christ, S. Amiriparian, A. Kathan, N. Müller, A. König, B. W. Schuller, "Multimodal Prediction of Spontaneous Humour: A Novel Dataset and First Results". arXiv preprint at arXiv: 2209.14272 [3] ] L. Christ, S. Amiriparian, A. Baird, P. Tzirakis, A. Kathan, N. Müller, L. Stappen, E.-M. Meßner, A. König, A. Cowen, E. Cambria, and B. W. Schuller, "The Muse 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress" in MuSe’22: Proceedings of the 3rd Multimodal Sentiment Analysis Workshop and Challenge. Lisbon, Portugal: Association for Computing Machinery, 2022, pp. 5–14, co-located with ACM Multimedia 2022, to appear. [4] S. Amiriparian, L. Christ, A. König, E.-M. Meßner, A. Cowen, E. Cambria, and B. W. Schuller, “Muse 2022 challenge: Multimodal humour, emotional reactions, and stress,” in Proceedings of the 30th ACM International Conference on Multimedia (MM’22). Lisbon, Portugal: Association for Computing Machinery, October 2022, 3 pages, to appear.

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Keywords

Humor, Audiovisual, Multimodal, Transcripts, Humour

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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