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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Qi Li Parthasarathy, S. Rosenberg, A.E. Tufts, D.W. | 
| Copyright Year | 1996 | 
| Description | Author affiliation: Speech Res. Dept., AT&T Bell Labs., Murray Hill, NJ, USA (Qi Li) | 
| Abstract | A modified linear discriminant analysis technique for speaker verification, referred to as normalized discriminant analysis (NDA), is presented. Using this technique it is possible to design an efficient linear classifier with very limited training data and to generate normalized discriminant scores with comparable magnitudes for different classifiers. The NDA technique is applied to a classifier for speaker verification based on speaker specific information obtained when utterances are processed with speaker independent models. In experiments conducted on a network based telephone database, the NDA technique provides an equal-error rate of 6.13% while the classifier using Fisher linear discriminant analysis has an equal-error rate of 18.18%. Furthermore, when the NDA combined with HMM approach in a hybrid speaker verification system, the rate was reduced from 5.30% (HMM with cohort normalization) to 4.32%. | 
| Starting Page | 681 | 
| Ending Page | 684 | 
| File Size | 373054 | 
| Page Count | 4 | 
| File Format | |
| ISBN | 0780331923 | 
| ISSN | 15206149 | 
| DOI | 10.1109/ICASSP.1996.543212 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 1996-05-09 | 
| Publisher Place | USA | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Hidden Markov models Training data Linear discriminant analysis Testing Speech analysis Telephony Ear Spatial databases Disk recording | 
| Content Type | Text | 
| Resource Type | Article | 
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