TY - GEN
T1 - Speech Emotion Recognition from Spectrograms with Deep Convolutional Neural Network
AU - Badshah, Abdul Malik
AU - Ahmad, Jamil
AU - Rahim, Nasir
AU - Baik, Sung Wook
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/3/20
Y1 - 2017/3/20
N2 - This paper presents a method for speech emotion recognition using spectrograms and deep convolutional neural network (CNN). Spectrograms generated from the speech signals are input to the deep CNN. The proposed model consisting of three convolutional layers and three fully connected layers extract discriminative features from spectrogram images and outputs predictions for the seven emotions. In this study, we trained the proposed model on spectrograms obtained from Berlin emotions dataset. Furthermore, we also investigated the effectiveness of transfer learning for emotions recognition using a pre-trained AlexNet model. Preliminary results indicate that the proposed approach based on freshly trained model is better than the fine-tuned model, and is capable of predicting emotions accurately and efficiently.
AB - This paper presents a method for speech emotion recognition using spectrograms and deep convolutional neural network (CNN). Spectrograms generated from the speech signals are input to the deep CNN. The proposed model consisting of three convolutional layers and three fully connected layers extract discriminative features from spectrogram images and outputs predictions for the seven emotions. In this study, we trained the proposed model on spectrograms obtained from Berlin emotions dataset. Furthermore, we also investigated the effectiveness of transfer learning for emotions recognition using a pre-trained AlexNet model. Preliminary results indicate that the proposed approach based on freshly trained model is better than the fine-tuned model, and is capable of predicting emotions accurately and efficiently.
KW - convolutional neural network
KW - emotions
KW - speech
UR - http://www.scopus.com/inward/record.url?scp=85018171150&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018171150&partnerID=8YFLogxK
U2 - 10.1109/PlatCon.2017.7883728
DO - 10.1109/PlatCon.2017.7883728
M3 - Conference contribution
AN - SCOPUS:85018171150
T3 - 2017 International Conference on Platform Technology and Service, PlatCon 2017 - Proceedings
BT - 2017 International Conference on Platform Technology and Service, PlatCon 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Platform Technology and Service, PlatCon 2017
Y2 - 13 February 2017 through 15 February 2017
ER -