Gender Recognition Using Deep Neural Networks

Voice gender recognition plays an important role in speech-processing systems and voice-based identity recognition systems. Due to the tremendous growth of artificial intelligence technologies and computer systems, voice data can be classified using deep neural networks to recognize the gender of the speaker. The voice gender recognition system with accent and English language has been investigated and implemented before, but despite the huge difference between the language, dialect, and accent of English and Persian, this work was done on the Persian dataset for the first time. In this research, deep neural networks ۱D-CNN, ۲D-CNN, LSTM, GRU, and SimpleRNN were used to classify the voice data set for the purpose of recognition and recognition, Finally, a ۲D-CNN neural network with ۹۹% accuracy is known as the best neural network for voice gender detection

کلیدواژه ها:

Voice Processing ، Gender Recognition ، Deep Neural Networks ، Deep Learning ، speech processing