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題名 Pronunciation variants in Thai preschool children learning Mandarin
作者 萬依萍
Wan, I-Ping;Marc, Allassonnière-Tang
貢獻者 語言所
關鍵詞 Pronunciation variants; Mandarin learning; Error analysis; Interlanguage
日期 2023-11
上傳時間 15-Mar-2024 11:16:45 (UTC+8)
摘要 The aim of the research is to provide a corpus-based and data-driven analysis of the learners' production in the target language at an early stage of the interlanguage system. Data were drawn from a spoken corpus constructed in Praat, which has been annotated and labeled in a semi-automatic approach by employing a wide range of applications in hybrid deep learning neural networks (Hybrid-DNN-HMM). The data extracted from the spoken corpus involve 36,565 tokens from Thai preschool children learning Mandarin in Bangkok, Thailand. The findings suggest the following: 1) Most of the learning errors do not reflect the phone existence in learners' native language; 2) Phone errors are more influential by the target language, and marked phones result in more errors between target and native languages; 3) Interlanguage can be described as a self-organizing and self-adaptive system. Contrastive analysis hypothesis, Markedness Differential Hypothesis, and Interlanguage theory will be discussed.
關聯 The Proceeding of 2023 International Conference on Asian Language Processing, Chinese and Oriental Languages Information Processing Society (COLIPS), pp.149-153
資料類型 conference
DOI https://doi.org/10.1109/IALP61005.2023.10336975
dc.contributor 語言所-
dc.creator (作者) 萬依萍-
dc.creator (作者) Wan, I-Ping;Marc, Allassonnière-Tang-
dc.date (日期) 2023-11-
dc.date.accessioned 15-Mar-2024 11:16:45 (UTC+8)-
dc.date.available 15-Mar-2024 11:16:45 (UTC+8)-
dc.date.issued (上傳時間) 15-Mar-2024 11:16:45 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/150485-
dc.description.abstract (摘要) The aim of the research is to provide a corpus-based and data-driven analysis of the learners' production in the target language at an early stage of the interlanguage system. Data were drawn from a spoken corpus constructed in Praat, which has been annotated and labeled in a semi-automatic approach by employing a wide range of applications in hybrid deep learning neural networks (Hybrid-DNN-HMM). The data extracted from the spoken corpus involve 36,565 tokens from Thai preschool children learning Mandarin in Bangkok, Thailand. The findings suggest the following: 1) Most of the learning errors do not reflect the phone existence in learners' native language; 2) Phone errors are more influential by the target language, and marked phones result in more errors between target and native languages; 3) Interlanguage can be described as a self-organizing and self-adaptive system. Contrastive analysis hypothesis, Markedness Differential Hypothesis, and Interlanguage theory will be discussed.-
dc.format.extent 111 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) The Proceeding of 2023 International Conference on Asian Language Processing, Chinese and Oriental Languages Information Processing Society (COLIPS), pp.149-153-
dc.subject (關鍵詞) Pronunciation variants; Mandarin learning; Error analysis; Interlanguage-
dc.title (題名) Pronunciation variants in Thai preschool children learning Mandarin-
dc.type (資料類型) conference-
dc.identifier.doi (DOI) 10.1109/IALP61005.2023.10336975-
dc.doi.uri (DOI) https://doi.org/10.1109/IALP61005.2023.10336975-