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What is Emotion Recognition in German Texts about?

This article discusses a novel approach for domain-generalized emotion recognition in German text corpora, addressing limitations in existing studies that primarily focus on specific domains and lexicon-based methods. The proposed methodology combines neural machine translation, weak supervision, and multi-view learning using the BERT model, achieving an F1-score of 65.5% and an accuracy of 68.1%. The findings aim to provide a benchmark for emotion recognition in German texts, facilitating further research

Author

Regina Stempel

Language

EN