Bengali Continuous Speech Voice-Based Gender Classification
Tofayel Ahamed Topu, Sunzida Siddique, Abu Kaisar Mohammad Masum, Sharun Akter Khushbu, S.M. Saiful Islam Badhon, Sheikh Abujar · 2021
An end-to-end process achieved by the convenient transformation of any purpose. Throughout this knowledge has been implemented by language advancement. In language, machine advancement happens in two ways one is text script processing, another is speech-based processing. A dual-language processing system is much needed for system development. Thus, Language processing over Bangla language is necessary for modernization because of the sub-continent most of the people use as a spoken language. We propose an identification by feature extraction from audio speech voice which is automatic speech recognition. Our model was proposed by supervised learning on continuous speech extraction over audio speech. Due to the outcome of this analysis, many fraud analyses will be possible. The purpose of model learning had used more than two hundred speakers on a voice synthesizer. All features and selected features were both identified with the frequency of male and female. Based on the different classifier performances the highest one is SVM acquired 98.48% also the nearest second is XG-boost.