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@article{1807940,
author = {Holaj, Richard and Pořízka, Petr},
article_number = {2},
doi = {http://dx.doi.org/10.2478/jazcas-2021-0047},
keywords = {pronunciation; L2; Czech; machine learning; neural networks; e-learning; annotation; speech recognition; automatic feedback; phonetics},
language = {eng},
issn = {0021-5597},
journal = {Jazykovedný časopis},
title = {L2 Czech Annotation for Automatic Feedback on Pronunciation},
url = {http://korpus.juls.savba.sk/attachments/slovko/Jazykovedny-casopis-2021-no2-SLOVKO_2.pdf},
volume = {72},
year = {2021}
}
TY - JOUR
ID - 1807940
AU - Holaj, Richard - Pořízka, Petr
PY - 2021
TI - L2 Czech Annotation for Automatic Feedback on Pronunciation
JF - Jazykovedný časopis
VL - 72
IS - 2
SP - 510-519
EP - 510-519
SN - 00215597
KW - pronunciation
KW - L2
KW - Czech
KW - machine learning
KW - neural networks
KW - e-learning
KW - annotation
KW - speech recognition
KW - automatic feedback
KW - phonetics
UR - http://korpus.juls.savba.sk/attachments/slovko/Jazykovedny-casopis-2021-no2-SLOVKO_2.pdf
N2 - In this paper, we would like to provide a brief overview of the current state of pronunciation teaching in e-learning and demonstrate a new approach to building tools for automatic feedback concerning correct pronunciation based on the most frequent or typical errors in speech production made by non-native speakers. We will illustrate this in the process of designing annotation for a sound recognition tool to provide feedback on pronunciation. At the end of the paper, we will also present how we have tried to apply this annotation to the tool, what caveats we have found and what our plans are.
ER -
HOLAJ, Richard and Petr POŘÍZKA. L2 Czech Annotation for Automatic Feedback on Pronunciation. \textit{Jazykovedný časopis}. 2021, vol.~72, No~2, p.~510-519. ISSN~0021-5597. Available from: https://dx.doi.org/10.2478/jazcas-2021-0047.
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