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
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
