<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

L2 Czech Annotation for Automatic Feedback on Pronunciation

Department of Czech Studies, Faculty of Arts

Journal of Linguistics/Jazykovedný casopis

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"L2 Czech Annotation for Automatic Feedback on Pronunciation"}

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...

L2 Czech Annotation for Automatic Feedback on Pronunciation

Published Online: Dec 30, 2021

Page range: 510 - 519

DOI: https://doi.org/10.2478/jazcas-2021-0047

Keywords
pronunciation, L2, Czech, machine learning, neural networks, e-learning, annotation, speech recognition, automatic feedback, phonetics

© 2021 Richard Holaj et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

L2 Czech Annotation for Automatic Feedback on Pronunciation

Published Online: Dec 30, 2021

Page range: 510 - 519

DOI: https://doi.org/10.2478/jazcas-2021-0047

Keywordspronunciation, L2, Czech, machine learning, neural networks, e-learning, annotation, speech recognition, automatic feedback, phonetics

© 2021 Richard Holaj et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
pronunciation, L2, Czech, machine learning, neural networks, e-learning, annotation, speech recognition, automatic feedback, phonetics