title: Phonetically optimized speaker modeling for robust speaker recognition.
abstract: This paper proposes an efficient method to improve speaker recognition performance by dynamically controlling the ratio of phoneme class information. It utilizes the fact that each phoneme contains different amounts of speaker discriminative information that can be measured by mutual information. After classifying phonemes into five classes, the optimal ratio of each class in both training and testing processes is adjusted using a non-linear optimization technique, i.e., the Nelder-Mead method. Speaker identification results verify that the proposed method achieves 18% improvement in terms of error rate compared to a baseline system.
authors.affiliation: Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemoon-gu, Seoul, Korea. lbjcom@dsp.yonsei.ac.kr
authors.forename: Bong-Jin
authors.initials: BJ
authors.lastname: Lee
authors.forename: Jeung-Yoon
authors.initials: JY
authors.lastname: Choi
authors.forename: Hong-Goo
authors.initials: HG
authors.lastname: Kang
mesh_terms: D000465:Algorithms; D000818:Animals; D007257:Information Theory; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D046709:Pattern Recognition, Physiological; D010700:Phonetics; D013060:Speech