@inproceedings{8d5f682be0574384a0979cd5813474a1,
title = "An open-set speaker identification system using genetic learning classifier system",
abstract = "This paper presents the design and implementation of an adaptive open-set speaker identification system with genetic learning classifier systems. One of the challenging problems in using learning classifier systems for numerical problems is the knowledge representation. The voice samples are a series of real numbers that must be encoded in a classifier format. We investigate several different methods for representing voice samples for classifier systems and study the efficacy of the methods. We also identify several challenges for learning classifier systems in the speaker identification problem and introduce new methods to improve the learning and classification abilities of the systems. Experimental results show that our system successfully learns 200 voice features at the accuracies of 60% to 80%, which is considered a strong result in the speaker identification community. This research presents the feasibility of using learning classifier systems for the speaker identification problem.",
keywords = "Classifier systems, Genetic algorithms, Language and speech, Linguistics, Machine learning",
author = "Park, {Won Kyung} and Blowers, {Misty K.} and Oh, {Jae C.} and Wolf, {Matt B.}",
year = "2006",
doi = "10.1145/1143997.1144259",
language = "English (US)",
isbn = "1595931864",
series = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery (ACM)",
pages = "1597--1598",
booktitle = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
address = "United States",
note = "8th Annual Genetic and Evolutionary Computation Conference 2006 ; Conference date: 08-07-2006 Through 12-07-2006",
}