对话中的结构:韵律的词汇、语义和句法的证据

IF 9.4 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Nadav Matalon, Eyal Weinreb, Dominik Freche, Erez Volk, Tirza Biron, Elisha Moses, David Biron
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引用次数: 0

摘要

拟声词是语音的音乐部分,在人类交流中举足轻重,其结构和含义仍是持续研究的主题。在本研究中,我们基于对自发会话的大规模分析,引入了一个数据驱动的英语前音模型。首先,我们识别了约 200 种可辨别的前音模式--我们将其视为前音词汇的基石--并概述了它们的特性和意义范围。接下来,我们揭示了一种类似于语法的马尔可夫逻辑,用于将这些基本构件连接成连贯的语句。我们确定了与成对的连续模式相关的独特复合功能,并表明马尔可夫语法在自发前音中比在脚本语音中更为普遍。这些发现为我们深入了解会话拟声的内在机制提供了宝贵的启示:它们为现有的理论概念提供了经验信息并对其进行了完善。我们提出的方法结合了对大型自发语音数据集的无监督分析和对结果的人工采样,可以指导未来的研究,旨在完善我们的模型并将其扩展到其他语言。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure in conversation: Evidence for the vocabulary, semantics, and syntax of prosody
Prosody, the musical facet of speech, is pivotal in human communication, and its structure and meaning remain subjects of ongoing research. In this study, we introduce a data-driven model for English prosody, based on large-scale analysis of spontaneous conversations. As a first step, we identify approximately 200 discernible prosodic patterns—which we view as building blocks of the prosodic vocabulary—and outline their properties and range of meanings. Next, we reveal a Markovian logic, akin to a syntax, for concatenating these elementary building blocks into coherent utterances. We identify distinct compound functions associated with pairs of consecutive patterns and show that the Markovian syntax is more prevalent in spontaneous prosody, as compared to scripted speech. These findings offer invaluable insights into the underlying mechanisms of conversational prosody: They empirically inform and refine existing theoretical concepts. The methodology we present, combining unsupervised analysis of large datasets of spontaneous speech with manual sampling of the results, could guide future research aimed at refining our model and expanding it to other languages.
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来源期刊
CiteScore
19.00
自引率
0.90%
发文量
3575
审稿时长
2.5 months
期刊介绍: The Proceedings of the National Academy of Sciences (PNAS), a peer-reviewed journal of the National Academy of Sciences (NAS), serves as an authoritative source for high-impact, original research across the biological, physical, and social sciences. With a global scope, the journal welcomes submissions from researchers worldwide, making it an inclusive platform for advancing scientific knowledge.
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