Exploring open consonantal environments for at-home testing of vowel perception in advanced L2 speakers

IF 2.1 2区 文学 0 LANGUAGE & LINGUISTICS Applied Linguistics Review Pub Date : 2022-11-29 DOI:10.1515/applirev-2021-0201
J. Jones
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Abstract

Abstract Recent work has called for increased investigation into methods used to explore second language (L2) speech perception (Flege 2021). The present study attends to this call, examining a common practice for developing listening prompts in the context of at-home administrations. Vowel perception studies have historically used fixed consonantal frames to determine how well participants can discriminate between target L2 vowels, and the present study compares the effects of employing a fixed consonant-vowel-consonant frame (h-vowel-d) with open (phonologically diverse) consonantal environments using real and nonce words. Thirty-eight Mandarin (n = 31) and English (n = 8) first language speakers participated in a listening experiment and a post-experiment question. Data were framed within Best and Tyler’s (2007) Perceptual Assimilation Model-L2. Internal consistency and proportion correct were calculated and a generalised linear mixed model design was used to investigate how well performance with h-vowel-d prompts predicts performance with the more diverse prompt types. Results suggest an inflation of scores for the fixed frame prompt and support the use of diverse words for listening prompt designs. Findings have implications for vowel perception researchers as well as computer (and mobile) assisted language learning developers wishing to inform their designs with relevant empirical evidence.
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探索开放的辅音环境,在家测试高级第二语言使用者的元音感知
摘要最近的工作呼吁加强对用于探索第二语言(L2)言语感知的方法的调查(Flege 2021)。本研究关注这一呼吁,研究了在家庭管理背景下开发听力提示的常见做法。元音感知研究历来使用固定的辅音框架来确定参与者在目标L2元音之间的辨别能力,本研究比较了使用固定辅音-元音-辅音框架(h-Vowel-d)与使用真实单词和非ce单词的开放(语音多样)辅音环境的效果。38名母语为普通话(n=31)和英语(n=8)的人参加了一项听力实验和一个实验后问题。数据是在Best和Tyler(2007)的感知同化模型L2中构建的。计算了内部一致性和比例正确性,并使用广义线性混合模型设计来研究h-vowel-d提示的性能如何预测更多样的提示类型的性能。结果表明,固定框架提示的分数膨胀,并支持在听力提示设计中使用不同的单词。研究结果对元音感知研究人员以及计算机(和移动)辅助语言学习开发人员都有启示,他们希望用相关的经验证据为自己的设计提供信息。
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来源期刊
CiteScore
4.20
自引率
7.70%
发文量
81
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