In this paper we present a speech rate estimator based on so-called rhythmicity features derived from a modified version of the short-time energy envelope. To evaluate the new method, it is compared to a traditional speech rate estimator on the basis of semi-automatic segmentation. Speech material from the Alcohol Language Corpus (ALC) covering intoxicated and sober speech of different speech styles provides a statistically sound foundation to test upon. The proposed measure clearly correlates with the semi-automatically determined speech rate and seems to be robust across speech styles and speaker states.
Bibliographic reference. Heinrich, Christian / Schiel, Florian (2011): "Estimating speaking rate by means of rhythmicity parameters", In INTERSPEECH-2011, 1873-1876.