Classification of English vowels in terms of Cypriot Greek categories: The role of acoustic similarity between L1 and L2 sounds

Georgios P. Georgiou
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引用次数: 3

Abstract

Previous evidence has suggested that acoustic similarity between first language (L1) and second language (L2) sounds is an accurate indicator of the speakers’ L2 classification patterns. This study investigates this assumption by examining how speakers of an under-researched language, namely Cypriot Greek, classify L2 English vowels in terms of their L1 categories. The experimental protocol relied on a perception and a production study. For the purpose of the production study, two linear discriminant analysis (LDA) models, one with both formants and duration (FD) and one with only formants (F) as input, were used to predict this classification; the models included data from both English and Cypriot Greek speakers. The perception study consisted of a classification task performed by adult Cypriot Greek advanced speakers of English who permanently resided in Cyprus. The results demonstrated that acoustic similarity was a relatively good predictor of speakers’ classification patterns as the majority of L2 vowels classified with the highest proportion were predicted with success by the LDA models. In addition, the F model was better than the FD model in predicting the full range of responses. This shows that duration features were less important than formant features for the prediction of L2 vowel classification.
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根据塞浦路斯希腊语类别对英语元音进行分类:L1 和 L2 声音相似性的作用
以往的证据表明,第一语言(L1)和第二语言(L2)声音之间的声学相似性是说话者 L2 分类模式的准确指标。本研究通过考察一种研究不足的语言(即塞浦路斯希腊语)的说话者如何根据其第一语言类别对第二语言英语元音进行分类,对这一假设进行了研究。实验方案依赖于感知和发音研究。在发音研究中,使用了两个线性判别分析(LDA)模型来预测这种分类,一个模型的输入包括元音和持续时间(FD),另一个模型的输入只有元音(F)。感知研究包括一项分类任务,由长期居住在塞浦路斯的成年塞浦路斯希腊语高级英语使用者完成。研究结果表明,声学相似性能较好地预测说话者的分类模式,因为 LDA 模型能成功预测出大部分分类比例最高的 L2元音。此外,在预测全部反应方面,F 模型优于 FD 模型。这表明,在预测 L2元音分类时,时长特征的重要性低于声旁特征。
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