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Author Steve, Vincent Wan
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Current State-of-the-art ♦ Support Vector Machine ♦ Polyvar Database ♦ Trained Gaussian Mixture Model ♦ Text Independent Speaker Verification ♦ Direct Discrimination ♦ Sequence-level Discrimination Approach ♦ Discriminative Classifier ♦ Score-space Kernel ♦ Complete Utterance
Abstract Support vector machines with the Fisher and score-space kernels are used for text independent speaker verification to provide direct discrimination between complete utterances. This is unlike approaches such as discriminatively trained Gaussian mixture models or other discriminative classifiers that discriminate at the frame-level only. Using the sequence-level discrimination approach we are able to achieve error-rates that are significantly better than the current state-of-the-art on the PolyVar database.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2003-01-01