Significance of Complementary Spectral Features for Speaker Recognition
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 8
Abstract
Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves.. The most popular features for speaker recognition are Mel frequency cepstral coefficients (MFCCs) and linear prediction cepstral Coefficients (LPCCs). These features are used extensively because they characterize the vocal tract configuration which is known. Motivated by the physiological significance of the vocal source and vocal tract system in speech production this paper present application of these feature as complementary information sources for a speaker recognition for improved performance and robustness. Speaker recognition makes it possible to user's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computersto be highly speakerdependent.
Authors and Affiliations
Piyush Lotia, Dr M R Khan
Keywords
Related Articles
- EP ID EP27625
- DOI -
- Views 283
- Downloads 4
Classification Of Heart Disease Using Svm And ANN
Classification of heart disease can be useful for the physicians if it is computerized for the purpose of fast diagnosis and accurate result. Predicting the existence of heart disease accurately can save patients life...
Multi Biometric Model for Authentication Method
In recent years, biometric authentication has seen considerable improvements in reliability and accuracy,with some biometrics contribute reasonably good overall performance. In biometric based systems for identity ve...
Effective R-cube Algorithm for Deriving Relevant Information on the Web
The analysis of user search goals can be very useful in improving search engine relevance and user experience. A novel approach to infer user search goals by examines search engine query logs. A framework to determin...
Smart Antennas Adaptive Beamforming through Statistical Signal Processing Techniques
The smart antenna improves the performance of wireless communication systems by increasing channel capacity and spectrum efficiency, extending range of coverage, steering multiple beams to track several mobiles. Smar...
An Energy Balanced Routing Method Based On Adaptive Heed for Wireless Sensor Networks
We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximit...