  Homophony's widespread presence in natural languages is a controversial
topic. Recent theories of language optimality have tried to justify its
prevalence, despite its negative effects on cognitive processing time; e.g.,
Piantadosi et al. (2012) argued homophony enables the reuse of efficient
wordforms and is thus beneficial for languages. This hypothesis has recently
been challenged by Trott and Bergen (2020), who posit that good wordforms are
more often homophonous simply because they are more phonotactically probable.
In this paper, we join in on the debate. We first propose a new
information-theoretic quantification of a language's homophony: the sample
R\'enyi entropy. Then, we use this quantification to revisit Trott and Bergen's
claims. While their point is theoretically sound, a specific methodological
issue in their experiments raises doubts about their results. After addressing
this issue, we find no clear pressure either towards or against homophony -- a
much more nuanced result than either Piantadosi et al.'s or Trott and Bergen's
findings.

Computation and Language