Applied Webservices Platform Supported Through Modified Edit Distance Algorithm: Automated Phonetic Transcription Grading Tool (APTgt)

Seals, Cheryl; Li, Sicheng; Atkins, Marisha Speights; Bailey, Dallin J.; Liu, Jueting; Cao, Yang; Bassy, Robertson

doi:10.1007/978-3-030-50513-4_29

Cited by 6 publications

(3 citation statements)

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“…Automated Phonetic Transcription-The Grading Tool (APTgt) is a well-designed interactive web-based E-learning system that focuses on phonetic transcription for students (learners) and teachers (faculty). Phonetic transcription is a process that represents the speech sounds using special characters or symbols [3].…”

Section: Linguistic E-learningmentioning

confidence: 99%

“…In a previous work, we developed an interactive E-learning system focused on phonetic transcription and pronunciation for language learners. This system, named APTgt, is an online exam system that provides phonetic transcription exams for IPA language students and automated grading tools for teachers [3]. To improve the intelligence and extensibility of the original system, in this paper, we propose three enhancements for the system based on machine learning and deep learning technology.…”

Section: Introductionmentioning

confidence: 99%

“…The primary system includes two parts: in the teacher's part, a teacher can create a question by attaching an audio file of word/phrase pronunciation and uploading its corresponding phonetic format as the answer; the student listens to the questions and types the answers on an IPA keyboard. The system then automatically calculates the similarity between the student's answers and the prestored correct answer using the edit distance algorithm and generates the grade [3,4].…”

Section: Introductionmentioning

confidence: 99%

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AI Enhancements for Linguistic E-Learning System

Liu,

Li,

Ren

et al. 2023

Applied Sciences

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E-learning systems have been considerably developed after the COVID-19 pandemic. In our previous work, we developed a linguistic interactive E-learning system for phonetic transcription learning. In this paper, we propose three artificial-intelligence-based enhancements to this system from different aspects. Compared with the original system, the first enhancement is a disordered speech classification module; this module is driven by the MFCC-CNN model, which aims to distinguish disordered speech and nondisordered speech. The accuracy of the classification is about 83%. The second enhancement is a grapheme-to-phoneme converter. This converter is based on the transformer model and designed for teachers to better generate IPA words from the regular written text. Compared with other G2P models, our transformer-based G2P model provides outstanding PER and WER performance. The last part of this paper focuses on a Tacotron2-based IPA-to-speech synthesis system, this deep learning-based TTS system can help teacher generate high-quality speech sounds from IPA characters which significantly improve the functionality of our original system. All of these three enhancements are related to the phonetic transcription process. and 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.

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Section: Linguistic E-learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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