Abstract
AbstractRecently, gender recognition has become an important area of research. Gender recognition can be used in various fields like for security purposes, speaker identification and speaker recognition. Various techniques has been used to identify the gender of person like using facial analysis, voice identification, machine learning, deep learning, using features like LPC and MFCC. This paper deals with identifying the gender using Acoustic properties of voice using Machine learning and how the accuracy vary when dataset goes through different transformation. It shows that we achieve maximum accuracy when uniform transformation is applied on dataset in case of KNN and SVM both.KeywordsAcoustic featuresMFCCLPCKNNSVMUniform distributionNormalizationGaussian distribution
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