Conference paper

D'HARO Luis Fernando, GLEMBEK Ondřej, PLCHOT Oldřich, MATĚJKA Pavel, SOUFIFAR Mehdi Mohammad, CORDOBA Ricardo and ČERNOCKÝ Jan. Phonotactic Language Recognition using i-vectors and Phoneme Posteriogram Counts. In: Proceedings of Interspeech 2012. Portland, Oregon: International Speech Communication Association, 2012, pp. 1-4. ISBN 978-1-62276-759-5. ISSN 1990-9772. Available from: http://www.isca-speech.org/archive/interspeech_2012/i12_0042.html
Publication language:english
Original title:Phonotactic Language Recognition using i-vectors and Phoneme Posteriogram Counts
Title (cs):Fonotaktické rozpoznávání jazyka využívající i-vektory a počty z fonémových posteriogramů
Pages:1-4
Proceedings:Proceedings of Interspeech 2012
Conference:Interspeech 2012
Place:Portland, Oregon, US
Year:2012
URL:http://www.isca-speech.org/archive/interspeech_2012/i12_0042.html
ISBN:978-1-62276-759-5
Journal:Proceedings of Interspeech, Vol. 2012, No. 9, FR
ISSN:1990-9772
Publisher:International Speech Communication Association
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2012/d_haro_interspeech2012_558_pp1_4.pdf [PDF]
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2012/d_haro_interspeech2012_presentation_MonO1b_04.pdf [PDF]
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2012/d_haro_interspeech2012_presentation_Mon.O1b.04.pptx [PPT]
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Keywords
subspace modeling, multinomial distributions, LID
Annotation
The article is about a Phonotactic Language Recognition using i-vectors and Phoneme Posteriogram Counts.
Abstract
This paper describes a novel approach to phonotactic LID, where instead of using soft-counts based on phoneme lattices, we use posteriogram to obtain n-gram counts. The high-dimensional vectors of counts are reduced to low-dimensional units for which we adapted the commonly used term i-vectors. The reduction is based on multinomial subspace modeling and is designed to work in the total-variability space. The proposed technique was tested on the NIST 2009 LRE set with better results to a system based on using soft-counts (Cavg on 30s: 3.15% vs 3.43%), and with very good results when fused with an acoustic i-vector LID system (Cavg on 30s acoustic 2.4% vs 1.25%). The proposed technique is also compared with another low dimensional projection system based on PCA. In comparison with the original soft-counts, the proposed technique provides better results, reduces the problems due to sparse counts, and avoids the process of using pruning techniques when creating the lattices.
BibTeX:
@INPROCEEDINGS{
   author = {Fernando Luis D'Haro and Ond{\v{r}}ej Glembek and
	Old{\v{r}}ich Plchot and Pavel Mat{\v{e}}jka and Mohammad
	Mehdi Soufifar and Ricardo Cordoba and Jan
	{\v{C}}ernock{\'{y}}},
   title = {Phonotactic Language Recognition using i-vectors and Phoneme
	Posteriogram Counts},
   pages = {1--4},
   booktitle = {Proceedings of Interspeech 2012},
   journal = {Proceedings of Interspeech},
   volume = {2012},
   number = {9},
   year = {2012},
   location = {Portland, Oregon, US},
   publisher = {International Speech Communication Association},
   ISBN = {978-1-62276-759-5},
   ISSN = {1990-9772},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=10093}
}

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