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An Efficient GMM Classification Post-Processing Method for Structural Gaussian Mixture Model Based Speaker Verification
- Source :
- ICASSP (1)
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
Abstract
- In this paper a Gaussian mixture model (GMM) classifier, called GMM identifier, is proposed as an efficient post-processing method to enhance the performance of a CMM-based speaker verification system; such as Gaussian mixture model universal background model (GMM-UBM) and structural Gaussian mixture models with structural background model (SGMM-SBM) speaker verification schemes. The proposed classifier shows good performance while its computational load is almost negligible compared to the main GMM system. Experimental results show the superior performance of this post-processing method in comparison with a neural-network post-processor for such applications.
- Subjects :
- Speaker verification
business.industry
Computer science
Speech recognition
Pattern recognition
Mixture model
Speaker recognition
Speech processing
Processing methods
symbols.namesake
ComputingMethodologies_PATTERNRECOGNITION
symbols
Artificial intelligence
business
Classifier (UML)
Gaussian process
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings
- Accession number :
- edsair.doi...........c6537c95297b4a850e1601447c670b07