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Working Together: Contributions of Corpus Analyses and Experimental Psycholinguistics to Understanding Conversation

机译:一起工作:语料库分析和实验心理语言学对理解会话的贡献

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摘要

As conversation is the most important way of using language, linguists and psychologists should combine forces to investigate how interlocutors deal with the cognitive demands arising during conversation. Linguistic analyses of corpora of conversation are needed to understand the structure of conversations, and experimental work is indispensable for understanding the underlying cognitive processes. We argue that joint consideration of corpus and experimental data is most informative when the utterances elicited in a lab experiment match those extracted from a corpus in relevant ways. This requirement to compare like with like seems obvious but is not trivial to achieve. To illustrate this approach, we report two experiments where responses to polar (yeso) questions were elicited in the lab and the response latencies were compared to gaps between polar questions and answers in a corpus of conversational speech. We found, as expected, that responses were given faster when they were easy to plan and planning could be initiated earlier than when they were harder to plan and planning was initiated later. Overall, in all but one condition, the latencies were longer than one would expect based on the analyses of corpus data. We discuss the implication of this partial match between the data sets and more generally how corpus and experimental data can best be combined in studies of conversation.
机译:由于对话是使用语言的最重要方式,因此语言学家和心理学家应该结合力量,研究对话者如何应对对话过程中产生的认知需求。进行对话语料库的语言分析是了解对话结构的必要条件,而实验工作对于理解潜在的认知过程是必不可少的。我们认为,当在实验室实验中引起的话语与以相关方式从语料库中提取的话语相匹配时,对语料库和实验数据的共同考虑最为有用。与“喜欢”进行比较的要求似乎很明显,但并非不易实现。为了说明这种方法,我们报告了两个实验,其中在实验室中引起了对极性(是/否)问题的回答,并将响应潜伏期与会话语音语料库中的极性问题和答案之间的差距进行了比较。我们发现,正如预期的那样,在易于计划和可以较早地开始计划时,要比在较难计划和较晚才开始计划时得到更快的响应。总体而言,在除一种情况外的所有情况下,等待时间都比基于语料库数据的分析所期望的要长。我们讨论了数据集之间这种部分匹配的含义,并且更广泛地讨论了如何在会话研究中将语料库和实验数据最好地结合起来。

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