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Start Over Contributor Czech Science Foundation@@19-26934X@@Neural Representations in Multi-modal and Multi-lingual Modelling@@nationalFunds@@ Contributor European Union@@H2020-ICT-2018-2-825460@@ELITR - European Live Translator@@euFunds@@info:eu-repo/grantAgreement/EC/H2020/825460 Rights Creative Commons - Attribution 4.0 International (CC BY 4.0) Harvested from LINDAT/CLARIAH-CZ repository

1. A Speech Test Set of Practice Business Presentations with Additional Relevant Texts

Creator:
Macháček, Dominik, Kratochvíl, Jonáš, Vojtěchová, Tereza, and Bojar, Ondřej
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
audio and corpus
Subject:
ASR, ASR evaluation, speech corpus, non-native English, speech recognition, speech recognition evaluation, speech and relevant texts, and European non-native English
Language:
English
Description:
We present a test corpus of audio recordings and transcriptions of presentations of students' enterprises together with their slides and web-pages. The corpus is intended for evaluation of automatic speech recognition (ASR) systems, especially in conditions where the prior availability of in-domain vocabulary and named entities is benefitable. The corpus consists of 39 presentations in English, each up to 90 seconds long, and slides and web-pages in Czech, Slovak, English, German, Romanian, Italian or Spanish. The speakers are high school students from European countries with English as their second language. We benchmark three baseline ASR systems on the corpus and show their imperfection.
Rights:
Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

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  • Czech Science Foundation@@19-26934X@@Neural Representations in Multi-modal and Multi-lingual Modelling@@nationalFunds@@1
  • European Union@@H2020-ICT-2018-2-825460@@ELITR - European Live Translator@@euFunds@@info:eu-repo/grantAgreement/EC/H2020/8254601