Superregular grammars do not provide additional explanatory power but allow for a compact analysis of animal song

• Published in: Royal Society open science Vol. 6; no. 7; p. 190139
• Main Authors: Morita, T, Koda, H
• Format: Journal Article
• Language: English
• Published: England The Royal Society 01-07-2019
• Subjects: animal song; bayesian analysis; Biology (Whole Organism); context-free grammar; gibbon; language; animal song; gibbon; language; Bayesian analysis; context-free grammar
• ISSN: 2054-5703; 2054-5703
• DOI: 10.1098/rsos.190139

A pervasive belief with regard to the differences between human language and animal vocal sequences (
) 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.