A broad survey of emotion recognition and generation across three modalities, but its reliability is hampered by misreported comparative results and citation errors.
XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection
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abstract
We introduce XED, a multilingual fine-grained emotion dataset. The dataset consists of human-annotated Finnish (25k) and English sentences (30k), as well as projected annotations for 30 additional languages, providing new resources for many low-resource languages. We use Plutchik's core emotions to annotate the dataset with the addition of neutral to create a multilabel multiclass dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to show that XED performs on par with other similar datasets and is therefore a useful tool for sentiment analysis and emotion detection.
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Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities
A broad survey of emotion recognition and generation across three modalities, but its reliability is hampered by misreported comparative results and citation errors.