Scopus Indexed Publications
Paper Details
- Title
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Bengali Continuous Speech Voice-Based Gender Classification
- Author
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Tofayel Ahamed Topu,
Abu Kaisar Mohammad Masum,
Sharun Akter Khushbu,
Sheikh Abujar,
S. M. Saiful Islam Badhon,
Sunzida Siddique,
- Email
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- Abstract
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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.
- Keywords
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Bengali language , audio speech voice , svm , xg-boost
- Journal or Conference Name
- 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
- Publication Year
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2021
- Indexing
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scopus