A Study of Correction Training for English Pronunciation Errors Through Deep Learning
DOI:
https://doi.org/10.31449/inf.v47i10.5391Abstract
In the process of globalization, English has become an essential skill. This article provides a brief introduction to the recognition process of English pronunciation errors based on deep learning. In the recognition process, the audio features of pronunciation were combined with the video features of lip movements during pronunciation to improve error detection performance. Subsequently, simulation experiments were conducted on the error detection algorithm, and a case analysis was performed on 100 freshmen from Hui College at Hebei Normal University to verify the effectiveness of the algorithm in correcting pronunciation. The results showed that the long short-term memory (LSTM) algorithm based on audio and video converged the fastest during training and had the smallest loss function. Additionally, it achieved the highest accuracy in phoneme recognition and pronunciation error detection, while being less affected by noise interference. After using the pronunciation error detection algorithm proposed in this article for oral correction training, students' pronunciation was significantly improved.
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
