Speaker verification method and apparatus using mixture decomposition discrimination
AssigneeLucent Technologies Inc.
InventorsMalan Bhatki Gandhi, Anand Rangaswamy Setlur, Rafid Antoon Sukkar
Life of this patent
Estimating the term…
Loading patent…
AssigneeLucent Technologies Inc.
InventorsMalan Bhatki Gandhi, Anand Rangaswamy Setlur, Rafid Antoon Sukkar
Estimating the term…
A new speaker verification method, termed Mixture Decomposition Discrimination (MDD), and a new apparatus for using MDD are presented. MDD takes mixture component score information from a speaker independent recognizer and transmits this information while it is still decomposed as a mixture of component scores that indicate the response of the states of a Hidden Markov Model (HMM) before this information is combined into a single speaker independent recognizer parameter. MDD can be very effective in improving the performance of existing verification methods based on speaker dependent HMMs with cohort normalization because the errors of the two speaker verification methods are very uncorrelated statistically. Experimental results have shown that when MDD is incorporated into a system that also uses speaker dependent HMMs, the resulting hybrid system has its average equal error rate reduced by 46% compared to cohort normalized speaker independent HMMs. MDD is used with a speaker dependent linear discriminator which has relatively low computational and storage requirements. Thus, the increased performance of a hybrid MDD-Cohort Normalized HMM system may be achieved with minimal increase in computational and data storage assets.
An apparatus for speaker verification of an input word string, comprising:
A method of speaker verification, comprising the steps of:
A method for speaker verification from input speech that has been converted into electrical signals, comprising the steps of:
A method for speaker verification from input speech that has been converted into electrical signals, comprising the steps of:
Dependencies are inferred from the claim text.