Speaker age and gender recognition using 1D and 2D convolutional neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09153-0.pdf
Reference28 articles.
1. Alkhawaldeh RS (2019) DGR: gender recognition of human speech using one-dimensional conventional neural network. Sci Program. https://doi.org/10.1155/2019/7213717
2. Alnuaim AA, Zakariah M, Shashidhar C, Hatamleh WA, Tarazi H, Shukla PK, Ratna R (2022) Speaker gender recognition based on deep neural networks and ResNet50. Wirel Commun Mob Comput. https://doi.org/10.1155/2022/4444388
3. Bhangale KB, Mohanaprasad K (2021) A review on speech processing using machine learning paradigm. Int J Speech Technol 24:367–388. https://doi.org/10.1007/s10772-021-09808-0
4. Büyük O, Arslan ML (2018) Combination of long-term and short-term features for age identification from voice. Adv Electr Comput Eng 18(2):101–108. https://doi.org/10.4316/AECE.2018.02013
5. Ertam F (2019) An effective gender recognition approach using voice data via deeper LSTM networks. Appl Acoust 156:351–358. https://doi.org/10.1016/j.apacoust.2019.07.033
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1. Automatic Age and Gender Recognition Using Ensemble Learning;Applied Sciences;2024-08-06
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