Paper ID: 2203.16794

MMER: Multimodal Multi-task Learning for Speech Emotion Recognition

Sreyan Ghosh, Utkarsh Tyagi, S Ramaneswaran, Harshvardhan Srivastava, Dinesh Manocha

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.

Submitted: Mar 31, 2022