Author/Authors
ÇAVDARLI, Murat Uludağ Üniversitesi - Mühendislik Mimarlık Fakültesi, TÜRKİYE , ESKİDERE, Ömer Uludağ Üniversitesi - Teknik Bilimler Meslek Yüksekokulu - Mekatronik Programı, TÜRKİYE , ERTAŞ, Figen Uludağ Üniversitesi - Mühendislik Mimarlık Fakültesi, TÜRKİYE
Title Of Article
A comparison of training algorithms in speaker identification
شماره ركورد
28063
Abstract
In this study, training algorithms are compared in Gaussian mixture model (GMM) based a speaker identification system. The Expectation maximization (EM) algorithm has widely been used to estimation of GMM parameters. In this article, the k-means and LBG are applied to GMM in order to estimate the vector quantization training parameters. The EM, the k-means and LBG training algorithms are tested with TIMIT and NTMIT databases and are compared speaker identification performance. Furthermore, the EM and k-means algorithms which sensitive against model initialization values are found optimum model initialization values for databases.
From Page
143
NaturalLanguageKeyword
BM , LBG , k , means , Speaker identification , Gaussian mixture model
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
To Page
153
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
Link To Document