  We develop techniques for determining an explicit Berry-Esseen bound in the
Kolmogorov distance for the normal approximation of a ratio of Gaussian
functionals. We provide an upper bound in terms of the third and fourth
cumulants, using some novel techniques and sharp estimates for cumulants.
  As applications, we study the rate of convergence of the distribution of
discretized versions of minimum contrast and maximum likelihood estimators of
the drift parameter of the Ornstein-Uhlenbeck process. Moreover, we derive
upper bounds that are strictly sharper than those available in the literature.
