Gender Recognition Using Deep Neural Networks
سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 319
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
SETT05_008
تاریخ نمایه سازی: 27 اسفند 1401
چکیده مقاله:
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:
نویسندگان
Seyed Amirreza Kabodian
Department of Computer Engineering, Khorasgan Branch, Islamic Azad University, Esfahan, Iran
Nima Rajaeian
Digital Processing and Machine Vision Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran