Speaker recognition with polynomial classifiers

• Published in: IEEE transactions on speech and audio processing Vol. 10; no. 4; pp. 205 - 212
• Main Authors: Campbell, W.M., Assaleh, K.T., Broun, C.C.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2002; Institute of Electrical and Electronics Engineers
• Subjects: Access control; Algorithms; Applied sciences; Biometrics; Classifiers; Exact sciences and technology; Hidden Markov models; Information, signal and communications theory; Iterative algorithms; Iterative methods; Mathematical models; Polynomials; Scoring; Signal processing; Speaker recognition; Speech; Speech processing; Speech recognition; Statistical analysis; Telecommunications and information theory; Discriminant analysis; Database; Classifier; Polynomial method; Speaker recognition; Learning algorithm; Computational complexity; Speech processing
• ISSN: 1063-6676; 1558-2353
• DOI: 10.1109/TSA.2002.1011533

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.