  We propose a statistical model for natural language that begins by
considering language as a monoid, then representing it in complex matrices with
a compatible translation invariant probability measure. We interpret the
probability measure as arising via the Born rule from a translation invariant
matrix product state.

Computation and Language;Disordered Systems and Neural Networks;Machine Learning;Neural and Evolutionary Computing;Machine Learning