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タイトル: | Superregular grammars do not provide additional explanatory power but allow for a compact analysis of animal song |
著者: | Morita, T. Koda, H. |
著者名の別形: | 香田, 啓貴 |
キーワード: | Bayesian analysis gibbon context-free grammar animal song language |
発行日: | 1-Jul-2019 |
出版者: | Royal Society Publishing |
誌名: | Royal Society Open Science |
巻: | 6 |
号: | 7 |
論文番号: | 190139 |
抄録: | A pervasive belief with regard to the differences between human language and animal vocal sequences (song) is that they belong to different classes of computational complexity, with animal song belonging to regular languages, whereas human language is superregular. This argument, however, lacks empirical evidence since superregular analyses of animal song are understudied. The goal of this paper is to perform a superregular analysis of animal song, using data from gibbons as a case study, and demonstrate that a superregular analysis can be effectively used with non-human data. A key finding is that a superregular analysis does not increase explanatory power but rather provides for compact analysis: fewer grammatical rules are necessary once superregularity is allowed. This pattern is analogous to a previous computational analysis of human language, and accordingly, the null hypothesis, that human language and animal song are governed by the same type of grammatical systems, cannot be rejected. |
著作権等: | © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
URI: | http://hdl.handle.net/2433/245687 |
DOI(出版社版): | 10.1098/rsos.190139 |
PubMed ID: | 31417719 |
出現コレクション: | 学術雑誌掲載論文等 |
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