In: Jazykovedný časopis, vol. 72, no. 2
Richard Holaj - Petr Pořízka
Details:
Year, pages: 2021, 510 - 519
Language: eng
Keywords:
pronunciation, L2, Czech, machine learning, neural networks, e-learning, annotation, speech recognition, automatic feedback, phonetics
Original source URL: https://www.juls.savba.sk/ediela/jc/2021/2/jc21-02.pdf
Article type: Natural Language Processing and Corpus Building
About article:
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.
How to cite:
ISO 690:
Holaj, R., Pořízka, P. 2021. L2 Czech annotation for automatic feedback on pronunciation. In Jazykovedný časopis, vol. 72, no.2, pp. 510-519. ISSN 0021-5597. DOI: https://doi.org/10.2478/jazcas-2021-0047
APA:
Holaj, R., Pořízka, P. (2021). L2 Czech annotation for automatic feedback on pronunciation. Jazykovedný časopis, 72(2), 510-519. ISSN 0021-5597. DOI: https://doi.org/10.2478/jazcas-2021-0047
About edition: