Gender Identification from Bangla Name Using Machine Learning and Deep Learning Algorithms
springer
摘要
The names of people have a large significance in various types of computing applications. In general, people’s names usually have a potential distinction between genders. Detecting genders from names with higher accuracy could be very challenging for Bangla and English character-based Bangla names. In this article, we showed the machine learning and deep learning-based characterization system which can recognize sexual orientations from the Bangladeshi people’s names. The Bangla character-based name placed with an exceptionally higher exactness of 91% and for the English name, it was 89%. We likewise consolidated diverse machine learning and deep learning classifiers techniques like random forest, SVM, Naive Bayes, impact learning, CNN, LSTM, etc., to break down which calculations give better outcomes. Besides, a Python pre-trained model on gender identification by Bangla’s name has been revealed.
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关键词
Gender detection, Impact learning, CNN, LSTM, Machine learning classifiers, Deep neural network
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