International Journal of Engineering Research

B. Rama Subbaiah ¹, M. Suleman Basha ¹, B. Ravi Teja ¹

Affiliations
1 Dept. of IT, RGMCET, Nandyal, IN

Abstract

This paper describes person identity by fingerprint, Face recognition, and voice information using Biometrics tool. The person is modeled by their features using Gaussian Mixture Model (GMM). Bio metrics is frequently used in signal processing applications. Thus, we concentrated on the methodology of biometrics for person identification which is useful in industrial and military security systems. The statistical values are measured by GMM in pattern recognition, Face recognition, and voice Recognition. These statistical values will helps for modeling of person using Bio-metric technique. The voice features are mapped into a Mel-Frequency-Cepstral-Coefficients (MFCC) form. The process of indentifying a person using MFCC data is described in this paper.

Keywords

GMM, MFCC, Speaker Recognition, Fingerprint Recognition, Face Recognition, Healing.

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B. Ravi Teja ¹, M. Suleman Basha ¹, M. Rama Subbiah ¹

Affiliations
1 Dept. of IT, RGMCET, Nandyal, IN

Abstract

Underlying of speech data refers the speaker features which are useful in speech recognition, speech processing, speech coding, and speech clustering. We described a brief of the area of speaker recognition, speech applications, and their underlying techniques. The review of automatic speech recognition (ASR) will discuss some of the positive and negative aspects of speaker recognition technologies and also outline the potential trends in research, development and applications.

Keywords

ASR, HMMs, Speech Recognition, Speech Clustering.

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