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首页> 外文期刊>Cognition: International Journal of Cognitive Psychology >Word informativity influences acoustic duration: Effects of contextual predictability on lexical representation
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Word informativity influences acoustic duration: Effects of contextual predictability on lexical representation

机译：单词的信息性影响听觉持续时间：上下文可预测性对词汇表示的影响

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摘要

Language-users reduce words in predictable contexts. Previous research indicates that reduction may be stored in lexical representation if a word is often reduced. Because representation influences production regardless of context, production should be biased by how often each word has been reduced in the speaker's prior experience. This study investigates whether speakers have a context-independent bias to reduce low-informativity words, which are usually predictable and therefore usually reduced. Content word durations were extracted from the Buckeye and Switchboard speech corpora, and analyzed for probabilistic reduction effects using a language model based on spontaneous speech in the Fisher corpus. The analysis supported the hypothesis: low-informativity words have shorter durations, even when the effects of local contextual predictability, frequency, speech rate, and several other variables are controlled for. Additional models that compared word types against only other words of the same segmental length further supported this conclusion. Words that usually appear in predictable contexts are reduced in all contexts, even those in which they are unpredictable. The result supports representational models in which reduction is stored, and where sufficiently frequent reduction biases later production. The finding provides new evidence that probabilistic reduction interacts with lexical representation.
机译：语言用户在可预测的上下文中减少单词。先前的研究表明，如果一个单词经常被简化，则可以用词汇表述形式存储归约。由于表示会影响生产，而与上下文无关，因此在说话者的先前经验中，每个词减少的频率应使生产有偏差。这项研究调查说话者是否具有上下文无关的偏见，以减少通常是可预测的并因此减少的低信息性单词。从七叶树和总机语音语料库中提取内容词的持续时间，并使用基于Fisher语料库中自发语音的语言模型分析概率减少效果。该分析支持以下假设：即使控制了局部上下文可预测性，频率，语速和其他几个变量的影响，低信息性单词的持续时间也较短。仅将单词类型与相同片段长度的其他单词进行比较的其他模型进一步支持了这一结论。通常在可预测的上下文中出现的单词在所有上下文中都会减少，即使在那些不可预测的单词中也是如此。结果支持代表性模型，在模型中存储了还原，并且足够频繁的还原会使以后的生产产生偏差。这一发现提供了新的证据，表明概率约简与词汇表述相互作用。

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