Enhancing the Performance of a GMM-based Speaker Identification System in a Multi-Microphone Setup

被引：0

作者：

Stergiou, Andreas ^{[1
]}

Pnevmatikakis, Aristodemos ^{[1
]}

Polymenakos, Lazaros C. ^{[1
]}

机构：

[1] Athens Informat Technol, Auton & Grid Comp Grp, Athens, Greece

来源：

INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, VOLS 1-5 | 2006年

关键词：

far-field speaker identification; gaussian mixture models; principal component analysis; microphone arrays;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper the speaker identification system developed at Athens Information Technology is presented. It is based on the Gaussian Mixture modeling of the Mel-Frequency Cepstral Coefficients of speech. Starting from this basic algorithm, we describe and discuss two significant modifications that have resulted in performance enhancements, in terms of both processing speed and identification accuracy. We present the performance of our system in the recent CLEAR 2006 evaluation workshop and also discuss approaches to further improve our system by fusing decisions derived from a multitude of sensors in a multi-microphone setup.

引用

页码：1463 / 1466

页数：4

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