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7 March 2022 A speech emotion recognition method for the elderly based on feature fusion and attention mechanism
Qijian Jian, Min Xiang, Wei Huang
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Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 121671O (2022) https://doi.org/10.1117/12.2628643
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China
Abstract
Aiming at the low accuracy of elderly speech emotion recognition, we propose an emotion recognition method that integrates the elderly's speech features and embeds the attention mechanism in this paper. The method firstly extracts the speech features of the elderly and fuse them. Then the fusion features are used as the bidirectional long and short-term memory network (BLSTM) input to learn the deep emotional features of each frame of speech. The attention mechanism uses to calculate the weight of the emotional classification of each frame feature. Finally, the features of each frame multiplied by their respective weight coefficient are used as the fully connected layer input to complete the recognition of speech emotion. The experimental results on the elderly speech emotion database (EESDB) show that compared with the traditional BLSTM, this method can effectively improve the accuracy of elderly speech emotion recognition.
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Qijian Jian, Min Xiang, and Wei Huang "A speech emotion recognition method for the elderly based on feature fusion and attention mechanism", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 121671O (7 March 2022); https://doi.org/10.1117/12.2628643
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KEYWORDS
Feature extraction
Data modeling
Signal processing
Neurons
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