Ajinkya N. Jadhav

Work place: Department of Computer science and Engineering, Rajarambapu Institute of Technology, Islampur 415414, India

E-mail: ajinkyajadhav.96@gmail.com


Research Interests: Computer systems and computational processes, Artificial Intelligence, Computational Learning Theory, Data Structures and Algorithms


Ajinkya N. Jadhav received the Bachelor of Engineering degree in Computer Science and Engineering, from Shivaji University. He has completed M. Tech. in Computer Science and Engineering from Rajarambapu Institute of Technology, Sakharale, Sangli, India. His area of interest is Artificial Intelligence, Machine Learning, and Web Development.

Author Articles
A Speaker Recognition System Using Gaussian Mixture Model, EM Algorithm and K-Means Clustering

By Ajinkya N. Jadhav Nagaraj V. Dharwadkar

DOI: https://doi.org/10.5815/ijmecs.2018.11.03, Pub. Date: 8 Nov. 2018

The automated speaker endorsement technique used for recognition of a person by his voice data. The speaker identification is one of the biometric recognition and they were also used in government services, banking services, building security and intelligence services like this applications. The exactness of this system is based on the pre-processing techniques used to select features produced by the voice and to identify the speaker, the speech modeling methods, as well as classifiers, are used. Here, the edges and continuous quality point are eliminated in the normalization process. The Mel-Scale Frequency Cepstral Coefficient is one of the methods to grab features from a wave file of spoken sentences. The Gaussian Mixture Model technique is used and done experiments on MARF (Modular Audio Recognition Framework) framework to increase outcome estimation. We have presented an end pointing elimination in Gaussian selection medium for MFCC.

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