  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.
