Sound change in the individual: Effects of exposure on cross-dialect speech processing

IF 1.3 2区 文学 0 LANGUAGE & LINGUISTICS Laboratory Phonology Pub Date : 2014-02-01 DOI:10.1515/lp-2014-0004
Cynthia G. Clopper
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引用次数: 28

Abstract

Abstract Speech perception is highly robust to variation, but familiarity with a particular source of variation can nevertheless lead to significant processing benefits. In the domain of cross-dialect speech perception, familiar local and standard varieties have been shown to facilitate lexical and semantic processing relative to unfamiliar dialects. However, more recent research suggests that individuals with exposure to both a local non-standard variety and a regional or national standard variety exhibit a mix of lexical processing costs and benefits, suggesting that familiarity with multiple different linguistic systems can result in both independent processing benefits for each variety as well as competition among variable multi-dialect representations. In an exemplar model of language processing, this complex pattern of results suggests several loci for sound change within an individual language user. Although the processing benefits associated with the local variety may contribute to long-term maintenance of variation through divergence from a regional or national standard, the processing benefits associated with the standard may contribute to dialect leveling and convergence towards the standard. Competition between these forces for maintenance and leveling will be observed most strongly in individuals with extensive exposure to both a non-standard local variety and a regional or national standard.
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个体的声音变化:暴露对跨方言语音加工的影响
语音感知对变化具有很强的鲁棒性,但熟悉特定的变化来源仍然可以带来显著的处理优势。在跨方言语音感知领域,熟悉的本地方言和标准方言相对于不熟悉的方言更容易促进词汇和语义处理。然而,最近的研究表明,接触当地非标准变体和地区或国家标准变体的个体表现出词汇加工成本和收益的混合,这表明熟悉多种不同的语言系统既会导致每种变体的独立加工收益,也会导致多种方言表征之间的竞争。在语言处理的范例模型中,这种复杂的结果模式表明,在单个语言使用者中,声音变化有几个位点。虽然与当地方言相关的加工利益可能有助于通过偏离地区或国家标准而长期保持差异,但与标准相关的加工利益可能有助于方言的平衡和向标准趋同。在广泛接触非标准本地品种和地区或国家标准的个体中,这些力量之间的维持和平衡竞争最为强烈。
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来源期刊
CiteScore
3.00
自引率
6.70%
发文量
17
审稿时长
8 weeks
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