An overview of text-independent speaker recognition: from features to supervectors

An overview of text-independent speaker recognition: from features to supervectors (2009)

by Tomi Kinnunen , Haizhou Li

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Datum	Value	Source
TITLE	An overview of text-independent speaker recognition: from features to supervectors	user correction
AUTHOR NAME	Tomi Kinnunen	user correction
AUTHOR AFFIL	Department of Computer Science and Statistics, Speech and Image Processing Unit	user correction
AUTHOR ADDR	University of Joensuu, P.O.Box 111, 80101 Joensuu, FINLAND	user correction
AUTHOR NAME	Haizhou Li	user correction
AUTHOR ADDR		user correction
ABSTRACT	This paper gives an overview of automatic speaker recognition technology, with an emphasis on text-independent recognition. Speaker recognition has been studied actively for several decades. We give an overview of both the classical and the state-of-the-art methods. We start with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling. We elaborate advanced computational techniques to address robustness and session variability. The recent progress from vectors towards supervectors opens up a new area of exploration and represents a technology trend. We also provide an overview of this recent development and discuss the evaluation methodology of speaker recognition systems. We conclude the paper with discussion on future directions.	SVM HeaderParse 0.2
YEAR	2009	user correction
CITATIONS	246 found	ParsCit 1.0