Analysis of Basic Emotions in Texts Based on BERT Vector Representation
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Abstract (arXiv)
In the following paper the authors present a GAN-type model and the most important stages of its development for the task of emotion recognition in text. In particular, we propose an approach for generating a synthetic dataset of all possible emotions combinations based on manually labelled incomplete data.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 21 Jan 2021.
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References · 3
- 2020GoEmotions: A Dataset of Fine-Grained Emotionscited by 479
- 2020A Sequence-to-Sequence Approach to Dialogue State Trackingcited by 43
- 2020A BERT-based Dual Embedding Model for Chinese Idiom Predictioncited by 4
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