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Speech emotion recognition (SER) is an important part of affective computing and signal processing research areas. A number of approaches, especially deep learning techniques, have achieved promising results on SER. However, there are still challenges in translating temporal and dynamic changes in emotions through speech. Spiking Neural Networks (SNN) have demonstrated as a promising approach in machine learning and pattern recognition tasks such as handwriting and facial expressiondoi:10.1109/ijcnn.2019.8852473 dblp:conf/ijcnn/Mansouri-Benssassi19 fatcat:by6d43nu5bfetbdrh5x6id6kuq