EMOTIONAL SPEECH RECOGNITION BASED ON CNN
Keywords:
Emotion Recognition, Audio Recognition, Feature Extraction, Convolutional Neural Network, Deep LearningAbstract
Recognition of emotional expressions during human–machine interaction has become quite popular due to its increasing application areas. Convolutional neural network (CNN) is a class of deep neural network and uses the advantage of pattern analysis of the data. This paper presents a robust speech emotion recognition system based on CNN. In the development of the proposed system, CNN based acoustic models are obtained by using speech processing, and artificial intelligence technologies. During the implementation stage, transfer learning and deep learning procedures have been used for feature extraction of speech datasets. The proposed system has been trained with features extracted from RAVDESS and SAVEE datasets. For implementation of the emotional speech system, Alex-Net is used. The experiments and performance evaluations are conducted to demonstrate the effectiveness of the proposed speech emotional system.
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Copyright (c) 2023 Selma OZAYDIN (Author)
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