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Speaker recognition with polynomial classifiers
Campbell W.M., , Broun C.C.
Published in IEEE
Volume: 10
Issue: 4
Pages: 205 - 212
Modern speaker recognition applications require high accuracy at low complexity. We propose the use of a polynomial-based classifier to achieve these objectives. This approach has several advantages. First, polynomial classifier scoring yields a system which is highly computationally scalable with the number of speakers. Second, a new training algorithm is proposed which is discriminative, handles large data sets, and has low memory usage. Third, the output of the polynomial classifier is easily incorporated into a statistical framework allowing it to be combined with other techniques such as hidden Markov models. Results are given for the application of the new methods to the YOHO speaker recognition database.
About the journal
JournalData powered by TypesetIEEE Transactions on Speech and Audio Processing
PublisherData powered by TypesetIEEE
Open AccessNo