Acknowledgement
본 연구는 과학기술정보통신부 및 한국연구재단의 기초연구사업 연구 결과로 수행되었음(RS-2023-00219107)
References
- 임명진, 이명호, 신주현, "상담 챗봇의 다차원 감정인식 모델," 스마트미디어저널, 제10권 제4호, 21-27쪽, 2021년 12월
- 이명호, 임명진, 신주현, "텍스트와 음성의 앙상블을 통한 다중 감정인식 모델," 스마트미디어저널, 제11권, 제8호, 65-72쪽, 2022년 09월 https://doi.org/10.30693/SMJ.2022.11.8.65
- H.J. Vogel, C. Suss, T. Hubregtsen, and E. Andre, "Emotion-awareness for intelligent vehicle assistants: A research agenda," Proc. of the 1st International Workshop on Software Engineering for AI in Autonomous Systems, pp. 11-15, Gothenburg, Swede, May. 2018.
- 임명진, 박원호, 신주현, "Word2Vec과 LSTM을 활용한 이별 가사 감정 분류," 스마트미디어저널, 제9권, 제3호, 90-97쪽, 2020년 9월 https://doi.org/10.30693/SMJ.2020.9.3.90
- J. Parry, D. Palaz, G. Clarke, P. Lecomte, R. Mead, M. Berger, and G. Hofer, "Analysis of Deep Learning Architectures for Cross-Corpus Speech Emotion Recognition," Interspeech, pp. 1656-1660, Graz, Austria, Sep. 2019.
- A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, L. Kaiser, and I. Polosukhin, "Attention is all you need," Proc, of Conference on Neural Information Processing Systems, pp. 5998-6008, Long Beach, California, USA, Dec. 2017.
- Z. Zhao, Q. Li, Z. Zhang, N. Cummins, H. Wang, J. Tao, and B.W. Schuller, "Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition," Neural Network, vol. 141, pp. 52-60, 2021. https://doi.org/10.1016/j.neunet.2021.03.013
- S. Sabour, N. Frosst, and G.E. Hinton, "Dynamic routing between capsules," Proc, of Conference on Neural Information Processing Systems, pp. 3856-3866, Long Beach, California, USA, Dec. 2017.
- F. Liu, S.Y. Shen, Z.W. Fu, H.Y. Wang, A.M. Zhou, and J.Y. Qi, "LGCCT: A light gated and crossed complementation transformer for multimodal speech emotion recognition," Entropy, vol. 24, no. 7, pp. 1010-1025, 2022. https://doi.org/10.3390/e24071010
- C.W. Wu, "ProdSumNet: reducing model parameters in deep neural networks via product-of-sums matrix decompositions," arXiv:1809.02209, 2018.
- J. Ye, X.C. Wen, Y. Wei, Y. Xu, K. Liu, and H. Shan, "Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition," arXiv:2211.08233, 2022.
- S. Zhang, S. Zhang, T. Huang, and W. Gao, "Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching," IEEE Transactions on Multimedia, vol. 20, no. 6, pp. 1576-1590, 2017. https://doi.org/10.1109/TMM.2017.2766843
- F. Burkhardt, A. Paeschke, M. Rolfes, W. Sendlmeier, and B. Weiss, "A Database of German Emotional Speech," Interspeech, pp. 1-4, Lisbon, Portugal, 2005.
- S.R Livingstone and F.A. Russo, "The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English," Plos one, vol. 13, no. 5, pp. e0196391, 2018.
- C. Busso, M. Bulut, C.C Lee, A. Kazemzadeh, E. Mower, S. Kim, J.N. Chang, S. Lee, and S.S narayanan, "IEMOCAP: Interactive emotional dyadic motion capture database," Language resources and evaluation, vol. 42, no. 4, pp. 335-359, 2008. https://doi.org/10.1007/s10579-008-9076-6
- P. Nantasri, E. Phaisangittisagul, J. Karnjana, S. Boonkla, S. Keerativittayanun, A. Rugchatjaroen, and T. Shinozaki, "A light-weight artificial neural network for speech emotion recognition using average values of MFCCs and their derivatives," 17th International conference on electrical engineering/electronics, computer, telecommunications and information technology (ECTI-CON), pp. 41-44, Phuket, Thailand, Jun. 2020.
- K. Atsavasirilert, T. Theeramunkong, S. Usanavasin, A. Rugchatjaroen, S. Boonkla, J. Karnjana, S. Keerativittayanun, and M. Okumura, "A light-weight deep convolutional neural network for speech emotion recognition using mel-spectrograms," 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP), pp. 1-4, Chiang Mai, Thailand, Oct. 2019.
- A. Krizhevsky, I. Sutskever, and G.E. Hinton, "Imagenet classification with deep convolutional neural networks," Communications of the ACM, vol. 60, no. 6, pp. 84-90, 2017. https://doi.org/10.1145/3065386
- J.X Ye, X.C. Wen, X.Z. Wang, Y. Xu, Y. Luo, C.L. Wu, L.Y. Chen, and K.H. Liu, "GM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition," Speech Communication, vol. 145, pp. 21-35, 2022. https://doi.org/10.1016/j.specom.2022.07.005
- J. L. Bautista, Y.K. Lee, and H.S. Shin, "Speech Emotion Recognition Based on Parallel CNN-Attention Networks with Multi-Fold Data Augmentation," Electronics, vol. 11, no. 23, pp. 3935-3949, 2022. https://doi.org/10.3390/electronics11233935
- D. Tang, P. Kuppens, L. Geurts, and T.V. Waterschoot, "End-to-end speech emotion recognition using a novel context-stacking dilated convolution neural network," EURASIP Journal on Audio, Speech, and Music Processing, vol. 2021, no. 1, pp. 1-16, 2021.
- S. Loffe and C. Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift," Proc 32nd International Conference on International Conference on Machine Learning, pp. 448-456, Lille, France, Jul. 2015.
- D.A. Clevert, T. Unterthiner, and S. Hochreiter, "Fast and accurate deep network learning by exponential linear units (ELUs)," arXiv:1511.07289, 2015.
- J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler "Efficient object localization using convolutional networks," Proc. of the IEEE conference on computer vision and pattern recognition, pp. 648-656, Boston, USA, Jun. 2015.
- B. McFee, C. Raffel, D. Liang, D.P.W. Ellis, M. McVicar, E. Battenberg, and O. Nieto, "librosa: Audio and Music Signal Analysis in Python," Proc. of the 14th python in science conference, pp. 18-25, Austin, Texas, USA, Jul. 2015.
- D.P. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," arXiv:1412.6980, 2014.
- B. Nagarajan and V.R.M. Oruganti, "Deep Learning as Feature Encoding for Emotion Recognition," arXiv:1810.12613 (2018).
- K. Chauhan, K.K. Sharma, and T. Varma, "Speech Emotion Recognition Using Convolution Neural Networks," international conference on artificial intelligence and smart systems (ICAIS), pp. 1176-1181, JTC College, Mar. 2021.
- X. Wu, S. Hu, Z. Wu, X. Liu, and H. Meng, "Neural Architecture Search for Speech Emotion Recognition," 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE, pp. 6902-6906, Singapore, May. 2022.