Person Authentication by voice and image using ANFIS and Shifted MFCC
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 8
Abstract
In security systems, the interest in using biometric technologies for person authentication has grown rapidly. Voice is one of the most promising and mature biometric modalities for secured access control. Here presents a novel approach to recognize/identify speakers with their images by including a new set of features and using Gaussian mixture models (GMMs). In this research, the concept of shifted MFCC is introduced so as to incorporate accent information in the recognition algorithm. VQ method is used for feature matching due to the ease of implementation and high accuracy. The goal of this project is to build a simple, yet complete and representative automatic speaker recognition system. Due to the limited space, we will only test our system on a very small speech database. The image of the speaker will also be displayed for further clarification. We can also hear the spelled word of each speaker in background while running the program. The algorithm showed improvements over the performance of the previous works.
Authors and Affiliations
Bhavyadas, Murugantham C, H S DivakaraMurthy, Parameshachari B D
Keywords
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