Conference paper

PLCHOT Oldřich, MATĚJKA Pavel, NOVOTNÝ Ondřej, CUMANI Sandro, LOZANO-DIEZ Alicia, SLAVÍČEK Josef, DIEZ Sánchez Mireia, GRÉZL František, GLEMBEK Ondřej, KAMSALI Veera Mounika, SILNOVA Anna, BURGET Lukáš, ONDEL Lucas, KESIRAJU Santosh and ROHDIN Johan A.. Analysis of BUT-PT Submission for NIST LRE 2017. In: Proceedings of Odyssey 2018 The Speaker and Language Recognition Workshop. Les Sables d'Olonne: International Speech Communication Association, 2018, pp. 47-53. ISSN 2312-2846.
Publication language:english
Original title:Analysis of BUT-PT Submission for NIST LRE 2017
Title (cs):Analýza BUT-PT systému pro NIST LRE 2017
Pages:47-53
Proceedings:Proceedings of Odyssey 2018 The Speaker and Language Recognition Workshop
Conference:Odyssey 2018
Place:Les Sables d'Olonne, FR
Year:2018
Journal:Proceedings of Odyssey: The Speaker and Language Recognition Workshop, Vol. 2018, No. 6, 4 Rue des Fauvettes - Lous Tourils, F-66390 BAIXAS, FR
ISSN:2312-2846
Publisher:International Speech Communication Association
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2018/plchot_odyssey2018_69.pdf [PDF]
Keywords
language recognition
Annotation
In this paper, we summarize our efforts in the NIST Language Recognition Evaluations (LRE) 2017 which resulted in systems providing very competitive and state-of-the-art performance. We provide both the descriptions and the analysis of the systems that we included in our submission. We explain our partitioning of the datasets that we were provided by NIST for training and development, and we follow by describing the features, DNN models and classifiers that were used to produce the final systems. After covering the architecture of our submission, we concentrate on post-evaluation analysis. We compare different DNN Bottle-Neck features, i-vector systems of different sizes and architectures, different classifiers and we present experimental results with data augmentation and with improved architecture of the system based on DNN embeddings. We present the performance of the systems in the Fixed condition (where participants are required to use only predefined data sets) and in addition to official NIST LRE17 evaluation set, we also provide results on our internal development set which can serve as a baseline for other researchers, since all training data are fixed and provided by NIST.
BibTeX:
@INPROCEEDINGS{
   author = {Old{\v{r}}ich Plchot and Pavel Mat{\v{e}}jka and
	Ond{\v{r}}ej Novotn{\'{y}} and Sandro Cumani and
	Alicia Lozano-Diez and Josef Slav{\'{i}}{\v{c}}ek
	and Mireia S{\'{a}}nchez Diez and Franti{\v{s}}ek
	Gr{\'{e}}zl and Ond{\v{r}}ej Glembek and Mounika
	Veera Kamsali and Anna Silnova and
	Luk{\'{a}}{\v{s}} Burget and Lucas Ondel and
	Santosh Kesiraju and A. Johan Rohdin},
   title = {Analysis of BUT-PT Submission for NIST LRE 2017},
   pages = {47--53},
   booktitle = {Proceedings of Odyssey 2018 The Speaker and Language
	Recognition Workshop},
   journal = {Proceedings of Odyssey: The Speaker and Language Recognition
	Workshop},
   volume = {2018},
   number = {6},
   year = {2018},
   location = {Les Sables d'Olonne, FR},
   publisher = {International Speech Communication Association},
   ISSN = {2312-2846},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=11762}
}

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