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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Siohan, O. Chin-Hui Lee Surendran, A.C. Qi Li |
| Copyright Year | 1999 |
| Description | Author affiliation: Lucent Technol., AT&T Bell Labs., Murray Hill, NJ, USA (Siohan, O.) |
| Abstract | Most state-of-the-art speaker verification systems need a user model built from samples of the customer speech, and a speaker independent (SI) background model with high acoustic resolution. These systems rely heavily on the availability of speaker independent databases along with a priori knowledge about acoustic rules of the utterance, and depend on the consistency of acoustic conditions under which the SI models were trained. These constraints may be a burden in practical and portable devices such as palm-top computers or wireless handsets which place a premium on computation and memory, and where the user is free to choose any password utterance in any language, under any acoustic condition. In this paper, we present a novel and reliable approach to background model design when only the enrollment data is available. Preliminary results are provided to demonstrate the effectiveness of such systems. |
| Starting Page | 825 |
| Ending Page | 828 |
| File Size | 416551 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780350413 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.1999.759798 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1999-03-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hidden Markov models Loudspeakers Acoustic devices Personal digital assistants Speech Portable computers Handheld computers Application software Natural languages Databases |
| Content Type | Text |
| Resource Type | Article |
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