The problem of vector quantizer empirical design for noisy channels or for noisy sources is studied. It is shown that the average squared distortion of a vector quantizer designed optimally from observing clean independent and identically distributed (i.i.d.) training vectors converges in expectation, as the training set size grows, to the minimum possible mean-squared error obtainable for quan...