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Original Article
NLP-Powered Emotion Analysis and ML-Driven Speech Processing with Flask
Thota Siva Naga Thirumalbabu1
Tungala Uma Mahesh2
P. Krishnaveni, M-Tech., (Ph.D)3
1 2 3 Department of Computer Science and Engineering, Sathyabhma Institute of Science and Technology Chennai, Tamilnadu, India.
Published Online: March-April 2026
Pages: 79-85
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20260602012
References
1. Ali, M. Hussain, and S. R. Al-Muhtaseb, "Deep learning- based facial expression recognition: A review and new perspectives," IEEE Access, vol. 8, pp. 165453-165470, 2020.
2. H. Ahn & J. Kim, "Deep facial expression recognition: A survey on recent advances," in IEEE Access, vol. 9, pp. 124288-124313, 2021.
3. G. Benitez-Garcia, H. Sanchez-Cruz, V. Sanchez, and T.-K. Kim, "Emotion recognition in the wild using deep neural networks," Sensors, vol. 20, no. 16, p. 4633, Aug. 2020.
4. J. Chen, Z. Chen, Z. Chi, and H. Fu, "Facial expression recognition using deep learning architectures: A review," IEEE Transactions on Affective Computing, vol. 13, no. 2, pp. 845-862, Apr.-Jun. 2022.
5. Y. Chen, J. Wang and X. Xu, "Multimodal emotion recognition with transformer-based fusion", in: V. T. Zygula, T. Schenk, and J. J. Pu, ed.: "Computing and Human Behaviour", vol. 25, p. 1234-1245, 2023, pp. 1234- 1245, in: "IEEE transactions on multimedia".
6. Corneanu, M. Madadi, and S. Escalera, "Overcoming data scarcity with transfer learning for facial expression analysis," in Proc. IEEE Int. Conf. Automatic Face & Gesture Recognition (FG), Buenos Aires, Argentina, 2021,pp. 79-86.
7. H. Ding, Y. Guo and H. Han, "Occlusion-robust facial expression recognition using attention-based CNNs," IEEE Transactions on Image Processing, vol. 31, pp. 1234-1248, Jan. 2022.
8. M. Elaina, M. Benimon and A. El-Sallam, "A hybrid CNN-LSTM model for facial expression recognition", Pattern Recognition, vol. 112, p. 107734, Mar. 2021.
9. X. Fan, L. Wang and Q. Ji, "Facial expression recognition in the wild with residual masking network", IEEE Transactions on Affective Computing, vol. 14, no. 1, pp. 34-48, Jan.-Mar. 2023.
10. Y. Gao, Y. Zhao, and L. Zhang, "Lightweight facial expression recognition using knowledge distillation," in the proceedings of the Association for Computing Machinery, Inc. Special Interest Group on Data Communication, vol. 10, no. 12, pp. 22215-22227, Dec.2022.
2. H. Ahn & J. Kim, "Deep facial expression recognition: A survey on recent advances," in IEEE Access, vol. 9, pp. 124288-124313, 2021.
3. G. Benitez-Garcia, H. Sanchez-Cruz, V. Sanchez, and T.-K. Kim, "Emotion recognition in the wild using deep neural networks," Sensors, vol. 20, no. 16, p. 4633, Aug. 2020.
4. J. Chen, Z. Chen, Z. Chi, and H. Fu, "Facial expression recognition using deep learning architectures: A review," IEEE Transactions on Affective Computing, vol. 13, no. 2, pp. 845-862, Apr.-Jun. 2022.
5. Y. Chen, J. Wang and X. Xu, "Multimodal emotion recognition with transformer-based fusion", in: V. T. Zygula, T. Schenk, and J. J. Pu, ed.: "Computing and Human Behaviour", vol. 25, p. 1234-1245, 2023, pp. 1234- 1245, in: "IEEE transactions on multimedia".
6. Corneanu, M. Madadi, and S. Escalera, "Overcoming data scarcity with transfer learning for facial expression analysis," in Proc. IEEE Int. Conf. Automatic Face & Gesture Recognition (FG), Buenos Aires, Argentina, 2021,pp. 79-86.
7. H. Ding, Y. Guo and H. Han, "Occlusion-robust facial expression recognition using attention-based CNNs," IEEE Transactions on Image Processing, vol. 31, pp. 1234-1248, Jan. 2022.
8. M. Elaina, M. Benimon and A. El-Sallam, "A hybrid CNN-LSTM model for facial expression recognition", Pattern Recognition, vol. 112, p. 107734, Mar. 2021.
9. X. Fan, L. Wang and Q. Ji, "Facial expression recognition in the wild with residual masking network", IEEE Transactions on Affective Computing, vol. 14, no. 1, pp. 34-48, Jan.-Mar. 2023.
10. Y. Gao, Y. Zhao, and L. Zhang, "Lightweight facial expression recognition using knowledge distillation," in the proceedings of the Association for Computing Machinery, Inc. Special Interest Group on Data Communication, vol. 10, no. 12, pp. 22215-22227, Dec.2022.
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