Earticle

초록

영어

Speech recognition is a challenging yet important speech technology. First, an introduction proposes components of typical automatic speaker recognition system .Two modes like enrollment mode and recognition is discussed. Then we discuss about Feature Extraction [8] .It is used to reduce the dimensionality of the input vector while maintaining the discriminating power of signal. After this Gaussian mixture modeling is discussed, which is the speaker modeling technique used in most systems. Vector Quantization Process is also discussed and then paper highlights on Supervectors. A few speaker modeling alternatives, namely, neural networks and support vector machines, are mentioned. Most recent technique to solve the Speaker Verification System is to combine GMM with SVM .So GMM Supervector [3] is also discussed. Here GMM supervector based SVM is applied to this field with spectral features. A GMM is trained for each utterance, and the corresponding GMM supervector is used as the input feature for SVM. Then, some applications of speaker verification are proposed, including on-site applications, remote applications, applications relative to structuring audio information, and games.

목차

Abstract
 1. Introduction
 2. Feature Extraction
 3. Gaussian Mixture Model
 4. Vector Quantization and Supervectors
 5. Support Vector Machine
 6. GMM Supervector
 7. GMM supervector based SVM Vss GMM
 8. Applications of Speaker Verification
  8.1 On-site Applications
  8.2 Remote Applications
  8.3 Information Structuring
  8.4 Games
 9. Conclusions and Future Trends
 References

키워드

저자

• Kauleshwar Prasad [ SSCET Bhilai, India ]
• Piyush Lotia [ SSCET Bhilai, India ]
• M. R. Khan [ GEC Raipur, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605