SpanEmo: Casting Multi-label Emotion Classification as Span-prediction

Understand

Emotion recognition (ER) is an important task in Natural Language Processing (NLP), due to its high impact in real-world applications from health and well-being to author profiling, consumer analysis and security.

• Current approaches to ER, mainly classify emotions independently without considering that emotions can co-exist.
• Such approaches overlook potential ambiguities, in which multiple emotions overlap.
• We propose a new model "SpanEmo" casting multi-label emotion classification as span-prediction, which can aid ER models to learn associations between labels and words in a sentence.