  Linguistic laws constitute one of the quantitative cornerstones of modern
cognitive sciences and have been routinely investigated in written corpora, or
in the equivalent transcription of oral corpora. This means that inferences of
statistical patterns of language in acoustics are biased by the arbitrary,
language-dependent segmentation of the signal, and virtually precludes the
possibility of making comparative studies between human voice and other animal
communication systems. Here we bridge this gap by proposing a method that
allows to measure such patterns in acoustic signals of arbitrary origin,
without needs to have access to the language corpus underneath. The method has
been applied to six different human languages, recovering successfully some
well-known laws of human communication at timescales even below the phoneme and
finding yet another link between complexity and criticality in a biological
system. These methods further pave the way for new comparative studies in
animal communication or the analysis of signals of unknown code.
