Article
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Preserved in Portico This version is not peer-reviewed
AI Enhancements for Linguistic E-learning System
Version 1
: Received: 19 September 2023 / Approved: 19 September 2023 / Online: 20 September 2023 (09:59:40 CEST)
A peer-reviewed article of this Preprint also exists.
Liu, J.; Li, S.; Ren, C.; Lyu, Y.; Xu, T.; Wang, Z.; Chen, W. AI Enhancements for Linguistic E-Learning System. Appl. Sci. 2023, 13, 10758. Liu, J.; Li, S.; Ren, C.; Lyu, Y.; Xu, T.; Wang, Z.; Chen, W. AI Enhancements for Linguistic E-Learning System. Appl. Sci. 2023, 13, 10758.
Abstract
The E-learning system has achieved great development after the pandemic. In this work, we proposed three artificial intelligence-based enhancements to our linguistic interactive E-learning system from different aspects. Compared with the original phonetic transcription exam system, our enhancements include an MFCC+CNN-based disordered speech classification module, a Transformer-based Grapheme-to-Phoneme converter, and a Tacotron2-based IPA-to-Speech speech synthesis system. This work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.
Keywords
linguistic E-learning; phonetic transcription; mel frequency cepstrum coefficient; grapheme-to-phoneme; transformer; speech synthesis
Subject
Computer Science and Mathematics, Other
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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