Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback
IntroductionTeaching English pronunciation in an English as a Second Language (ESL) context involves tailored strategies to help learners accurately produce sounds, intonation, and rhythm.MethodsThis study presents an innovative method utilizing advanced technology and algorithms to enhance pronunci...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1484630/full |
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| author | Li Ping Ning Tao |
| author_facet | Li Ping Ning Tao |
| author_sort | Li Ping |
| collection | DOAJ |
| description | IntroductionTeaching English pronunciation in an English as a Second Language (ESL) context involves tailored strategies to help learners accurately produce sounds, intonation, and rhythm.MethodsThis study presents an innovative method utilizing advanced technology and algorithms to enhance pronunciation accuracy, fluency, and completeness. The approach employs multi-sensor detection methods for precise data collection, preprocessing techniques such as pre-emphasis, normalization, framing, windowing, and endpoint detection to ensure high-quality speech signals. Feature extraction focuses on key attributes of pronunciation, which are then fused through a feedback neural network for comprehensive evaluation. The experiment involved 100 college students, including 50 male and 50 female students, to test their English pronunciation.ResultsEmpirical results demonstrate significant improvements over existing methods. The proposed method achieved a teaching evaluation accuracy of 99.3%, compared to 68.9% and 77.8% for other referenced methods. Additionally, students showed higher levels of fluency, with most achieving a level of 4 or above, whereas traditional methods resulted in lower fluency levels. Spectral feature analysis indicated that the amplitude of speech signals obtained using the proposed method closely matched the original signals, unlike the discrepancies found in previous methods.DiscussionThese findings highlight the effectiveness of the proposed method, showcasing its ability to improve pronunciation accuracy and fluency. The integration of multi-sensor detection and neural network evaluation provides precise results, outperforming traditional approaches. |
| format | Article |
| id | doaj-art-4c1ac3385313490d8826829b066fe26d |
| institution | Kabale University |
| issn | 1664-1078 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj-art-4c1ac3385313490d8826829b066fe26d2025-01-22T13:26:25ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-01-011510.3389/fpsyg.2024.14846301484630Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedbackLi Ping0Ning Tao1School of Foreign Languages, Jiangsu Ocean University, Lianyungang, ChinaSchool of Computer Engineering, Guilin University of Electronic Technology, Beihai, ChinaIntroductionTeaching English pronunciation in an English as a Second Language (ESL) context involves tailored strategies to help learners accurately produce sounds, intonation, and rhythm.MethodsThis study presents an innovative method utilizing advanced technology and algorithms to enhance pronunciation accuracy, fluency, and completeness. The approach employs multi-sensor detection methods for precise data collection, preprocessing techniques such as pre-emphasis, normalization, framing, windowing, and endpoint detection to ensure high-quality speech signals. Feature extraction focuses on key attributes of pronunciation, which are then fused through a feedback neural network for comprehensive evaluation. The experiment involved 100 college students, including 50 male and 50 female students, to test their English pronunciation.ResultsEmpirical results demonstrate significant improvements over existing methods. The proposed method achieved a teaching evaluation accuracy of 99.3%, compared to 68.9% and 77.8% for other referenced methods. Additionally, students showed higher levels of fluency, with most achieving a level of 4 or above, whereas traditional methods resulted in lower fluency levels. Spectral feature analysis indicated that the amplitude of speech signals obtained using the proposed method closely matched the original signals, unlike the discrepancies found in previous methods.DiscussionThese findings highlight the effectiveness of the proposed method, showcasing its ability to improve pronunciation accuracy and fluency. The integration of multi-sensor detection and neural network evaluation provides precise results, outperforming traditional approaches.https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1484630/fullaccuracyEnglish as a second languageEnglish pronunciationfeedback neural networkspeech signal processingteaching evaluation |
| spellingShingle | Li Ping Ning Tao Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback Frontiers in Psychology accuracy English as a second language English pronunciation feedback neural network speech signal processing teaching evaluation |
| title | Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback |
| title_full | Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback |
| title_fullStr | Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback |
| title_full_unstemmed | Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback |
| title_short | Innovative approaches to English pronunciation instruction in ESL contexts: integration of multi-sensor detection and advanced algorithmic feedback |
| title_sort | innovative approaches to english pronunciation instruction in esl contexts integration of multi sensor detection and advanced algorithmic feedback |
| topic | accuracy English as a second language English pronunciation feedback neural network speech signal processing teaching evaluation |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1484630/full |
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