  The Berry-Ess\'{e}en upper bounds of moment estimators and least squares
estimators of the mean and drift coefficients in Vasicek models driven by
general Gaussian processes are studied. When studying the parameter estimation
problem of Ornstein-Uhlenbeck (OU) process driven by fractional Brownian
motion, the commonly used methods are mainly given by Kim and Park, they show
the upper bound of Kolmogorov distance between the distribution of the ratio of
two double Wiener-It\^{o} stochastic integrals and the Normal distribution. The
main innovation in this paper is extending the above ratio process, that is to
say, the numerator and denominator respectively contain triple Wiener-It\^{o}
stochastic integrals at most. As far as we know, the upper bounds between the
distribution of above estimators and the Normal distribution are novel.
