Text-independent open-set speaker identification for military missions using genetic rule-based system | Zendy

Jae C. Oh | Zendy; Misty Blowers | Zendy

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Text-independent open-set speaker identification for military missions using genetic rule-based system

Author(s) -

Jae C. Oh,

Misty Blowers

Publication year - 2005

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/1102256.1102296

Subject(s) - computer science , classifier (uml) , cluster analysis , artificial intelligence , speaker recognition , open set , mel frequency cepstrum , speech recognition , speaker identification , speaker verification , set (abstract data type) , pattern recognition (psychology) , machine learning , feature extraction , mathematics , programming language , discrete mathematics

We present a genetic classifier system approach to the text-independent open-set speaker identification problem. Classifier systems are widely used in symbolic problem for dynamically changing open-ended learning. Signal processing problems require processing of real-valued parameters that classifier systems are not designed for. On the other hand, the approaches based on common cepstral encoding with clustering algorithms handle the closed-set speaker identification quite well. This research solves the open-set problem by hybridizing these two approaches.

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