Článek ve sborníku konference

 
Plchot, O., Karafiát, M., Brummer, N., Glembek, O., Matějka, P., de, V., E., Černocký, J.: Speaker vectors from Subspace Gaussian Mixture Model as complementary features for Language Identification, In: Proceedings of Odyssey 2012, The Speaker and Language Recognition Workshop, Singapur, SG, ISCA, 2012, s. 330-333, ISBN 978-981-07-3093-2
Jazyk publikace:angličtina
Název publikace:Speaker vectors from Subspace Gaussian Mixture Model as complementary features for Language Identification
Název (cs):Adaptační vektory mluvčího ze Subspace Gaussian Mixture modelu jako komplementární příznaky pro identifikaci jazyka
Strany:330-333
Sborník:Proceedings of Odyssey 2012, The Speaker and Language Recognition Workshop
Konference:Odyssey 2012: The Speaker and Language Recognition Workshop
Místo vydání:Singapur, SG
Rok:2012
ISBN:978-981-07-3093-2
Vydavatel:International Speech Communication Association
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2012/plchot_odyssey2012_330-333-41.pdf [PDF]
Klíčová slova
speaker recognition, Gaussian Mixture Model, speaker vectors, language identification
Anotace
V této publikaci jsme presentovali použití adaptačních vektorů mluvčího ze Subspace Gaussian Mixture modelu jako komplementárních příznaků pro rozpoznávání jazyka.
Abstrakt
In this paper, we explore new high-level features for language identification. The recently introduced Subspace Gaussian Mixture Models (SGMM) provide an elegant and efficient way for GMM acoustic modelling, with mean supervectors represented in a low-dimensional representative subspace. SGMMs also provide an efficient way of speaker adaptation by means of lowdimensional vectors. In our framework, these vectors are used as features for language identification. They are compared with our acoustic iVector system, which architecture is currently considered state-of-the-art for Language Identification and Speaker Verification. The results of both systems and their fusion are reported on the NIST LRE2009 dataset.
BibTeX:
@INPROCEEDINGS{
   author = {Oldřich Plchot and Martin Karafiát and Niko Brummer and
	Ondřej Glembek and Pavel Matějka and Edward Villiers de and
	Jan Černocký},
   title = {Speaker vectors from Subspace Gaussian Mixture Model as
	complementary features for Language Identification},
   pages = {330--333},
   booktitle = {Proceedings of Odyssey 2012, The Speaker and Language
	Recognition Workshop},
   year = {2012},
   location = {Singapur, SG},
   publisher = {International Speech Communication Association},
   ISBN = {978-981-07-3093-2},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=10056}
}