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[Author] Yuqi XIA(1hit)

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  • A Multitask Learning Approach Based on Cascaded Attention Network and Self-Adaption Loss for Speech Emotion Recognition

    Yang LIU  Yuqi XIA  Haoqin SUN  Xiaolei MENG  Jianxiong BAI  Wenbo GUAN  Zhen ZHAO  Yongwei LI  

     
    PAPER-Speech and Hearing

      Pubricized:
    2022/12/08
      Vol:
    E106-A No:6
      Page(s):
    876-885

    Speech emotion recognition (SER) has been a complex and difficult task for a long time due to emotional complexity. In this paper, we propose a multitask deep learning approach based on cascaded attention network and self-adaption loss for SER. First, non-personalized features are extracted to represent the process of emotion change while reducing external variables' influence. Second, to highlight salient speech emotion features, a cascade attention network is proposed, where spatial temporal attention can effectively locate the regions of speech that express emotion, while self-attention reduces the dependence on external information. Finally, the influence brought by the differences in gender and human perception of external information is alleviated by using a multitask learning strategy, where a self-adaption loss is introduced to determine the weights of different tasks dynamically. Experimental results on IEMOCAP dataset demonstrate that our method gains an absolute improvement of 1.97% and 0.91% over state-of-the-art strategies in terms of weighted accuracy (WA) and unweighted accuracy (UA), respectively.