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  4. A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis
 
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2022
Conference Paper
Title

A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis

Abstract
For research in audiovisual interview archives often it is not only of interest what is said but also how. Sentiment analysis and emotion recognition can help capture, categorize and make these different facets searchable. In particular, for oral history archives, such indexing technologies can be of great interest. These technologies can help understand the role of emotions in historical remembering. However, humans often perceive sentiments and emotions ambiguously and subjectively. Moreover, oral history interviews have multi-layered levels of complex, sometimes contradictory, sometimes very subtle facets of emotions. Therefore, the question arises of the chance machines and humans have capturing and assigning these into predefined categories. This paper investigates the ambiguity in human perception of emotions and sentiment in German oral history interviews and the impact on machine learning systems. Our experiments reveal substantial differences in human perception for different emotions. Furthermore, we report from ongoing machine learning experiments with different modalities. We show that the human perceptual ambiguity and other challenges, such as class imbalance and lack of training data, currently limit the opportunities of these technologies for oral history archives. Nonetheless, our work uncovers promising observations and possibilities for further research.
Author(s)
Gref, Michael  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Matthiesen, Nike
Haus der Geschichte der Bundesrepublik Deutschland Foundation (HdG)
Hikkal Venugopala, Sreenivasa
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Satheesh, Shalaka  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Vijayananth, Aswinkumar
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Ha, Duc Bach  orcid-logo
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Behnke, Sven  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Köhler, Joachim  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Mainwork
Language Resources and Evaluation Conference, LREC 2022. Conference Proceedings  
Conference
Language Resources and Evaluation Conference 2022  
Open Access
File(s)
Download (520.89 KB)
Rights
CC BY-NC 4.0: Creative Commons Attribution-NonCommercial
DOI
10.24406/publica-379
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • emotion recognition

  • sentiment analysis

  • language

  • oral history

  • speech emotion recognition

  • facial emotion recognition

  • annotation

  • ambiguity

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