📰 01 paper is accepted at The 15th International Conference on ICT Convergence (ICTC 2024), Jeju, Korea.

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Our paper titled "Voice-Based Age and Gender Recognition: A Comparative Study of LSTM, RezoNet, and Hybrid CNNs-BiLSTM Architecture" has been accepted for presentation at the 15th International Conference on ICT Convergence (ICTC 2024) in Jeju, Korea. This paper presents a detailed comparative study of various deep learning architectures, including LSTM, RezoNet, and a hybrid CNNs-BiLSTM model, focusing on their effectiveness in recognizing age and gender from voice data. The acceptance of this paper underscores the significance of our research in advancing the field of voice-based biometric recognition and contributes to the ongoing discussions on the intersection of deep learning and human-computer interaction.

• Nhut Minh Nguyen, Thanh Trung Nguyen, Hua Hiep Nguyen, Phuong-Nam Tran, and Dr. Duc Ngoc Minh Dang, “Voice-Based Age and Gender Recognition: A Comparative Study of LSTM, RezoNet and Hybrid CNNs-BiLSTM Architecture”, The 15th International Conference on ICT Convergence (ICTC 2024), Jeju, Korea