Large Corpus of Czech Parliament Plenary Hearings
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424461" target="_blank" >RIV/00216208:11320/20:10424461 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.lrec-1.781/" target="_blank" >https://www.aclweb.org/anthology/2020.lrec-1.781/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Large Corpus of Czech Parliament Plenary Hearings
Original language description
We present a large corpus of Czech parliament plenary sessions. The corpus consists of approximately 1200 hours of speech data and corresponding text transcriptions. The whole corpus has been segmented to short audio segments making it suitable for both training and evaluation of automatic speech recognition (ASR) systems. The source language of the corpus is Czech, which makes it a valuable resource for future research as only a few public datasets are available in the Czech language. We complement the data release with experiments of two baseline ASR systems trained on the presented data: the more traditional approach implemented in the Kaldi ASRtoolkit which combines hidden Markov models and deep neural networks (NN) and a modern ASR architecture implemented in Jaspertoolkit which uses deep NNs in an end-to-end fashion.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GX19-26934X" target="_blank" >GX19-26934X: Neural Representations in Multi-modal and Multi-lingual Modeling</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020)
ISBN
979-10-95546-34-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
6363-6367
Publisher name
European Language Resources Association
Place of publication
Marseille, France
Event location
Marseille, France
Event date
May 11, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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