  We propose a model of the speech perception of individual words in the
presence of mishearings. This phenomenological approach is based on concepts
used in linguistics, and provides a formalism that is universal across
languages. We put forward an efficient two-parameter form for the word length
distribution, and introduce a simple representation of mishearings, which we
use in our subsequent modelling of word recognition. In a context-free
scenario, word recognition often occurs via anticipation when, part-way into a
word, we can correctly guess its full form. We give a quantitative estimate of
this anticipation threshold when no mishearings occur, in terms of model
parameters. As might be expected, the whole anticipation effect disappears when
there are sufficiently many mishearings. Our global approach to the problem of
speech perception is in the spirit of an optimisation problem. We show for
instance that speech perception is easy when the word length is less than a
threshold, to be identified with a static transition, and hard otherwise. We
extend this to the dynamics of word recognition, proposing an intuitive
approach highlighting the distinction between individual, isolated mishearings
and clusters of contiguous mishearings. At least in some parameter range, a
dynamical transition is manifest well before the static transition is reached,
as is the case for many other examples of complex systems.
