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About Ser DRCNN
This paper proposes a new method called Deep Retinal Convolution Neural Networks (DRCNNs) for speech emotion recognition that combines data augmentation and deep learning. It uses a data augmentation algorithm based on the retinal imaging principle to generate spectrograms of different sizes from audio data in order to increase the amount of training data. It then uses deep convolutional neural networks to extract high-level features from the spectrograms and achieve highly accurate emotion recognition, obtaining over 99% average accuracy on multiple databases. Experimental results show this approach outperforms previous methods in terms of both number of emotions recognized and recognition accuracy.
Detailed Information
| Author: | ['Mohammed Ansaf'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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