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arXiv · 2203.16794

MMER: Multimodal Multi-task Learning for Speech Emotion Recognition

Sreyan Ghosh·Utkarsh Tyagi·S Ramaneswaran·Harshvardhan Srivastava·Dinesh Manocha
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Abstract

In this paper, we propose MMER, a novel Multimodal Multi-task learning approach for Speech Emotion Recognition. MMER leverages a novel multimodal network based on early-fusion and cross-modal self-attention between text and acoustic modalities and solves three novel auxiliary tasks for learning emotion recognition from spoken utterances. In practice, MMER outperforms all our baselines and achieves state-of-the-art performance on the IEMOCAP benchmark. Additionally, we conduct extensive ablation studies and results analysis to prove the effectiveness of our proposed approach.

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Sreyan Ghosh, Utkarsh Tyagi, S Ramaneswaran, Harshvardhan Srivastava, Dinesh Manocha. 2022-03-31. MMER: Multimodal Multi-task Learning for Speech Emotion Recognition. https://arxiv.org/abs/2203.16794

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