Abstract
Point of this paper is to style a gender reorganization system that distinguishes the gender of the agent. Gender classification is associate rising space of analysis for the accomplishment of economical interaction between human and machine victimization speech files. Numerous ways in which are planned for the gender classification within the past. Speech recognition is a chief approach for the identification of the supply. In this work different feature for the gender classification are gait of person, lips shape, automatic face recognition, iris code, etc. There aretwo experiments performed, the 1st experiment deals with the gender classification of ten completely different languages, every language consists of fifteen audio files and also the best accuracy achieved by the machine learning technique that's straight forward logistical (87.33%). The second experiment deals with the formation of language identification system within which Russian and Korean has the simplest combination of language with the a hundred accuracy by multilayer perceptron.
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Yadav, M., yadav, C.S., Kumar, R., Yadav, P.S. (2021). Gender Identification Over Voice Sample Using Machine Learning. In: Chaki, N., Pejas, J., Devarakonda, N., Rao Kovvur, R.M. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-15-8767-2_10
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DOI: https://doi.org/10.1007/978-981-15-8767-2_10
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