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语法语境的概率结构如何塑造言语。

How the Probabilistic Structure of Grammatical Context Shapes Speech.

作者信息

Linke Maja, Ramscar Michael

机构信息

Department of Linguistics, University of Tuebingen, Wilhelmstraße 19, 72074 Tuebingen, Germany.

出版信息

Entropy (Basel). 2020 Jan 11;22(1):90. doi: 10.3390/e22010090.

DOI:10.3390/e22010090
PMID:33285865
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7516525/
Abstract

Does systematic covariation in the usage patterns of forms shape the sublexical variance observed in conversational speech? We address this question in terms of a recently proposed discriminative theory of human communication that argues that the distribution of events in communicative contexts should maintain mutual predictability between language users, present evidence that the distributions of words in the empirical contexts in which they are learned and used are geometric, and thus support this. Here, we extend this analysis to a corpus of conversational English, showing that the distribution of grammatical regularities and the sub-distributions of tokens discriminated by them are also geometric. Further analyses reveal a range of structural differences in the distribution of types in parts of speech categories that further support the suggestion that linguistic distributions (and codes) are subcategorized by context at multiple levels of abstraction. Finally, a series of analyses of the variation in spoken language reveals that quantifiable differences in the structure of lexical subcategories appears in turn to systematically shape sublexical variation in speech signal.

摘要

形式使用模式中的系统协变是否塑造了在对话言语中观察到的次词汇变异?我们根据最近提出的一种关于人类交流的判别理论来探讨这个问题,该理论认为交流语境中事件的分布应在语言使用者之间保持相互可预测性,我们给出证据表明词语在其被学习和使用的经验语境中的分布是几何分布,从而支持这一观点。在此,我们将这种分析扩展到一个英语口语语料库,表明语法规则的分布以及由它们区分的词元子分布也是几何分布。进一步的分析揭示了词性类别中类型分布的一系列结构差异,这进一步支持了这样一种观点,即语言分布(和编码)在多个抽象层次上按语境进行了子分类。最后,对口语变异的一系列分析表明,词汇子类别结构中的可量化差异似乎又系统地塑造了语音信号中的次词汇变异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/5bd79f7b7090/entropy-22-00090-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/1d09242914ee/entropy-22-00090-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/a7a80a4444c6/entropy-22-00090-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/0efadc951f13/entropy-22-00090-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/b879cf7a4ce6/entropy-22-00090-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/c12fa8129f06/entropy-22-00090-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/872417590ac2/entropy-22-00090-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/9ad11e392721/entropy-22-00090-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/8e2cce4309e0/entropy-22-00090-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/5bd79f7b7090/entropy-22-00090-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/1d09242914ee/entropy-22-00090-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/a7a80a4444c6/entropy-22-00090-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/0efadc951f13/entropy-22-00090-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/b879cf7a4ce6/entropy-22-00090-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/c12fa8129f06/entropy-22-00090-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/872417590ac2/entropy-22-00090-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/9ad11e392721/entropy-22-00090-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/8e2cce4309e0/entropy-22-00090-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d2/7516525/5bd79f7b7090/entropy-22-00090-g009.jpg

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