Conference paper| PLCHOT Oldřich, MATĚJKA Pavel, SILNOVA Anna, NOVOTNÝ Ondřej, DIEZ Sánchez Mireia, ROHDIN Johan A., GLEMBEK Ondřej, BRÜMMER Niko, SWART Albert du Preez, PRIETO Jesús J., GARCIA Perera Leibny Paola, BUERA Luis, KENNY Patrick, ALAM Jahangir and BHATTACHARYA Gautam. Analysis and Description of ABC Submission to NIST SRE 2016. In: Proceedings of Interspeech 2017. Stockholm: International Speech Communication Association, 2017, pp. 1348-1352. ISSN 1990-9772. Available from: http://www.isca-speech.org/archive/Interspeech_2017/pdfs/1498.PDF | | Publication language: | english |
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| Original title: | Analysis and Description of ABC Submission to NIST SRE 2016 |
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| Title (cs): | Analýza a popis ABC systému pro NIST SRE 2016 |
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| Pages: | 1348-1352 |
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| Proceedings: | Proceedings of Interspeech 2017 |
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| Conference: | Interspeech 2017 |
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| Place: | Stockholm, SE |
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| Year: | 2017 |
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| URL: | http://www.isca-speech.org/archive/Interspeech_2017/pdfs/1498.PDF |
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| Journal: | Proceedings of Interspeech, Vol. 2017, No. 08, FR |
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| ISSN: | 1990-9772 |
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| DOI: | 10.21437/Interspeech.2017-1498 |
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| Publisher: | International Speech Communication Association |
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| URL: | http://www.fit.vutbr.cz/research/groups/speech/publi/2017/plchot_interspeech2017_IS171498.pdf [PDF] |
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| Keywords |
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| speaker recognition, i-vector, DNN, fusion |
| Annotation |
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| This article is about the analysis and description of ABC Submission to NIST SRE 2016.We have presented various sytems of the ABC team that are designed to cope with dataset mismatch and non-English data. We have presented and compared several fusion and calibration strategies and we have uncovered and discussed problems brought by SRE16. |
| Abstract |
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| We present a condensed description and analysis of the joint
submission for NIST SRE 2016, by Agnitio, BUT and CRIM
(ABC). We concentrate on challenges that arose during development
and we analyze the results obtained on the evaluation
data and on our development sets. We show that testing on
mismatched, non-English and short duration data introduced in
NIST SRE 2016 is a difficult problem for current state-of-theart
systems. Testing on this data brought back the issue of score
normalization and it also revealed that the bottleneck features
(BN), which are superior when used for telephone English, are
lacking in performance against the standard acoustic features
like Mel Frequency Cepstral Coefficients (MFCCs). We offer
ABCs insights, findings and suggestions for building a robust
system suitable for mismatched, non-English and relatively
noisy data such as those in NIST SRE 2016. |
| BibTeX: |
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@INPROCEEDINGS{
author = {Old{\v{r}}ich Plchot and Pavel Mat{\v{e}}jka and
Anna Silnova and Ond{\v{r}}ej Novotn{\'{y}} and
Mireia S{\'{a}}nchez Diez and A. Johan Rohdin and
Ond{\v{r}}ej Glembek and Niko Br{\"{u}}mmer and
Preez du Albert Swart and J. Jes{\'{u}}s Prieto
and Paola Leibny Perera Garcia and Luis Buera and
Patrick Kenny and Jahangir Alam and Gautam
Bhattacharya},
title = {Analysis and Description of ABC Submission to NIST
SRE 2016},
pages = {1348--1352},
booktitle = {Proceedings of Interspeech 2017},
journal = {Proceedings of Interspeech},
volume = {2017},
number = {08},
year = {2017},
location = {Stockholm, SE},
publisher = {International Speech Communication Association},
ISSN = {1990-9772},
doi = {10.21437/Interspeech.2017-1498},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php.en?id=11581}
} |
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Faculty of Information Technology
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