Deep learning has been widely adopted in automatic emotion recognition and has lead to significant progress in the field . However, due to insufficient annotated emotion datasets, pre-trained models are limited in their generalization capability and thus lead to poor performance on novel test sets… To mitigate this challenge, transfer learning performing fine-tuning on pre-training models has been applied . But, the pre-tuned knowledge may overwrite and/or discard important knowledge learned from models . In this paper, we address this issue by proposing a PathNet-based transfer learning method that is able to transfer emotional knowledge . to another visual/audio emotion domain, and transfer the . emotional knowledge learned . from multiple audio emotion domains into one another to improve overall emotion recognition accuracy . The experimental results indicate that our proposed system is capable of improving the . proposed system was capable of . improving the performance of emotion recognition, making its performance substantially superior to the recent proposed .

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Keywords : emotion - transfer - knowledge - learning - recognition -

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