@inproceedings{979b0d3407f947ec89afbf6e370c5886,
title = "Robust text-independent speaker identification using hybrid PCA&LDA",
abstract = "We have been building a text-independent speaker recognition system in noisy conditions. In this paper, we propose a novel feature using hybrid PCA/LDA. The feature is created from the convectional MFCC(mel-frequency cepstral coefficients) by transforming them using a matrix. The matrix consists of some components from the PCA and LDA transformation matrices. We tested the new feature using Aurora project Database 2 which is intended for the evaluation of algorithms for front-end feature extraction algorithms in background noise. The proposed method outperformed in all noise types and noise levels. It reduced the relative recognition error by 63.6% than using the baseline feature when the SNR is 15dB.",
author = "Kim, {Min Seok} and Yu, {Ha Jin} and Kwak, {Keun Chang} and Chi, {Su Young}",
year = "2006",
doi = "10.1007/11925231_102",
language = "English",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1067--1074",
booktitle = "MICAI 2006",
address = "Germany",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}