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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gedo, C.N. Eremic, J.C. |
| Copyright Year | 1991 |
| Description | Author affiliation: US Naval Postgraduate Sch., Monterey, CA, USA (Gedo, C.N.; Eremic, J.C.) |
| Abstract | A system is presented which will identify speakers that it was trained to recognize with 100% accuracy. This system will also classify inputs that it has not been trained to recognize as unknown. The high degree of confidence offered by this system is attributed to careful processing of the input data sets. Only easily distinguishable segments of the speech samples are passed as inputs to the artificial neural network (ANN). Additionally, sufficient input information is provided with the training inputs to enable the ANN to rapidly train and subsequently classify speakers. This system may be readily implemented in hardware using existing technology. Hardware implementation will render near real-time performance. Applications that would be enhanced by the use of this system include electronic surveillance and computer security. The speaker identification system was successfully tested. |
| Starting Page | 1151 |
| Ending Page | 1154 |
| File Size | 257333 |
| Page Count | 4 |
| File Format | |
| ISBN | 0818624701 |
| ISSN | 10586393 |
| DOI | 10.1109/ACSSC.1991.186628 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1991-11-04 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speaker recognition Discrete transforms Artificial neural networks Speech processing Hardware Sampling methods Frequency estimation Application software Surveillance Computer security |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Computer Networks and Communications |
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