  In this work, we present the misspecified Gaussian Cram\'er-Rao lower bound
for the parameters of a harmonic signal, or pitch, when signal measurements are
collected from an almost, but not quite, harmonic model. For the asymptotic
case of large sample sizes, we present a closed-form expression for the bound
corresponding to the pseduo-true fundamental frequency. Using simulation
studies, it is shown that the bound is sharp and is attained by maximum
likelihood estimators derived under the misspecified harmonic assumption. It is
shown that misspecified harmonic models achieve a lower mean squared error than
correctly specified unstructured models for moderately inharmonic signals.
Examining voices from a speech database, we conclude that human speech belongs
to this class of signals, verifying that the use of a harmonic model for voiced
speech is preferable.
