Speech technology enables computing statistics on word pronunciation variants as well as investigating various phonetic phenomena. This is achieved through a forced alignment of large amounts of speech signals with their possible pronunciations variants. Such alignments are usually performed using a 10 ms frame shift acoustical analysis. Therefore , the three emitting state structure of conventional acoustic hidden Markov models introduces a minimum duration constraint of 30 ms for each phone segment. This constraint is not critical at low speaking rates, but may introduce artefacts at high speaking rates. Thus, this paper investigates the impact of the acoustical frame rate on corpus-based phonetic statistics. Statistics on pronunciation variants obtained with a shorter frame shift (5 ms) are compared to the statistics resulting from the standard 10 ms frame shift. Statistics are computed on a large speech corpus of more than 3 million running words, and are analyzed with respect to the estimated local speaking rate. Results exhibit some discrepancies between the two sets of statistics, in particular for high speaking rates where the usual acoustic analysis frame shift of 10 ms leads to an underestimation of the frequency of the longest pronunciation variants.