TCS Research at SemEval-2018 Task 1 Learning Robust Representations using Multi-Attention Architecture

Model Architecture

Abstract

This paper presents system description of our submission to the SemEval-2018 task-1, Affect in tweets for the English language. We combine three different features generated using deep learning models and traditional methods in support vector machines to create a unified ensemble system. A robust representation of a tweet is learned using a multi-attention based architecture which uses a mixture of different pre-trained embeddings. In addition to this analysis of different features is also presented. Our system ranked 2nd, 5th, and 7th in different subtasks among 75 teams.

Publication
In Proceedings of The 12th International Workshop on Semantic Evaluation

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