Communicative efficiency in multimodal language directed at children and adults.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-07-01 Epub Date: 2024-06-06 DOI:10.1037/xge0001588
Beata Grzyb, Stefan L Frank, Gabriella Vigliocco
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Abstract

The ecology of human communication is face to face. In these contexts, speakers dynamically modify their communication across vocal (e.g., speaking rate) and gestural (e.g., cospeech gestures related in meaning to the content of speech) channels while speaking. What is the function of these adjustments? Here we ask whether speakers dynamically make these adjustments to increase communicative success, and decrease cognitive effort while speaking. We assess whether speakers modulate word durations and produce iconic (i.e., imagistically evoking properties of referents) gestures depending on the predictability of each word they utter. Predictability is operationalized as surprisal and computed from computational language models trained on corpora of child-directed, or adult-directed language. Using data from a novel corpus (Ecological Language Corpus) of naturalistic interactions between adult-child (aged 3-4), and adult-adult, we show that surprisal predicts speakers' multimodal adjustments and that some of these effects are modulated by whether the comprehender is a child or an adult. Thus, communicative efficiency applies generally across vocal and gestural communicative channels not being limited to structural properties of language or vocal modality. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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针对儿童和成人的多模态语言的交流效率。
人类交流的生态环境是面对面的。在这种情况下,说话者在说话时会动态地调整他们在声音(如语速)和手势(如与说话内容相关的共同言语手势)方面的交流。这些调整的作用是什么?在这里,我们要问的是,说话者是否会在说话时动态地进行这些调整,以提高交际成功率并减少认知努力。我们将评估说话者是否会根据他们说出的每个单词的可预测性来调整单词的持续时间并做出标志性(即通过想象唤起所指事物的属性)手势。可预测性被操作化为惊奇,并通过在儿童或成人语言语料库中训练的计算语言模型进行计算。通过使用来自成人-儿童(3-4 岁)和成人-成人之间自然互动的新型语料库(生态语言语料库)的数据,我们发现,惊奇可以预测说话者的多模态调整,而且其中一些效果会受到理解者是儿童还是成人的影响。因此,交际效率普遍适用于发声和手势交际渠道,而不局限于语言或发声方式的结构属性。(PsycInfo Database Record (c) 2024 APA, 版权所有)。
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CiteScore
7.20
自引率
4.30%
发文量
567
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