Conference paper

SILNOVA Anna, GLEMBEK Ondřej, KINNUNEN Tomi and MATĚJKA Pavel. Exploring ANN Back-Ends for i-Vector Based Speaker Age Estimation. In: Proceedings of Interspeech 2015. Dresden: International Speech Communication Association, 2015, pp. 3036-3040. ISBN 978-1-5108-1790-6. ISSN 1990-9772.
Publication language:english
Original title:Exploring ANN Back-Ends for i-Vector Based Speaker Age Estimation
Title (cs):Využití ANN klasifikátorů pro odhad věku řečníka založený na i-vektorech
Proceedings:Proceedings of Interspeech 2015
Conference:INTERSPEECH 2015
Place:Dresden, DE
Journal:Proceedings of Interspeech, Vol. 2015, No. 09, FR
Publisher:International Speech Communication Association
age estimation, i-vector, multilayer perceptron
This publication focuses on exploring artificial neural net (ANN) Back-Ends for i-Vector Based Speaker Age Estimation.
We address the problem of speaker age estimation using ivectors. We first compare different i-vector extraction setups and then focus on (shallow) artificial neural net (ANN) backends. We explore ANN architecture, training algorithm and ANN ensembles. The results on NIST 2008 and 2010 SRE data indicate that, after extensive parameter optimization, ANN back-end in combination with i-vectors reaches mean absolute errors (MAEs) of 5.49 (females) and 6.35 (males), which are 4.5% relative improvement in comparison to our support-vector regression (SVR) baseline. Hence, the choice of back-end did not affect the accuracy much; a suggested future direction is therefore focusing more on front-end processing.
   author = {Anna Silnova and Ond{\v{r}}ej Glembek and Tomi
	Kinnunen and Pavel Mat{\v{e}}jka},
   title = {Exploring ANN Back-Ends for i-Vector Based Speaker
	Age Estimation},
   pages = {3036--3040},
   booktitle = {Proceedings of Interspeech 2015},
   journal = {Proceedings of Interspeech},
   volume = 2015,
 number = 09,
   year = 2015,
   location = {Dresden, DE},
   publisher = {International Speech Communication Association},
   ISBN = {978-1-5108-1790-6},
   ISSN = {1990-9772},
   language = {english},
   url = {}

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