- Speaker identification from emotional and noisy speech using learned voice segregation and speech VGG. Expert Systems with Applications, 224, p.119871, 2023. Hamsa, S., Shahin, I., Iraqi, Y., Damiani, E., Nassif, A.B., and Werghi, N. [pdf] [demo]
- Emotion recognition from speech using wavelet packet transform cochlear filter bank and random forest classifier. IEEE Access, 8, pp.96994-97006, 2020. Hamsa, S., Shahin, I., Iraqi, Y., and Werghi, N. [pdf] [demo]
- An enhanced emotion recognition algorithm using pitch correlogram, deep sparse matrix representation and random forest classifier. IEEE Access, 9, pp.87995-88010, 2021. Hamsa, S., Iraqi, Y., Shahin, I., and Werghi, N. [pdf] [demo]
- Dominant voiced speech segregation and noise reduction pre-processing module for hearing aids and speech processing applications. In Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020), 12, pp. 395-403, Springer International Publishing, 2021. Hamsa, S., Iraqi, Y., Shahin, I., and Werghi, N. [pdf] [demo]
- EA-VGG: A new approach for emotional speech classification. 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), pp. 1-5, November 2022. Koya, S.H., Shahin, I., Iraqi, Y., Damiani, E., and Werghi, N. [pdf] [demo]
- COVID-19 detection systems using deep-learning algorithms based on speech and image data. Mathematics, 10(4), p.564, 2022. Nassif, A.B., Shahin, I., Bader, M., Hassan, A., and Werghi, N. [pdf] [demo]