Estimating the Speaking Rate by Vowel Detection

We present a new feature-based method for estimating the speaking rate by detecting vowels in continuous speech. The features used are the modified loudness and the zerocrossing rate which are both calculated in the standard preprocessing unit of our speech recognition system. As vowels in general correspond to syllable nuclei, the feature-based vowel rate is comparable to an estimate of the lexically-based syllable rate. The vowel detector presented is tested on the spontaneously spoken German Verbmobil task and is evaluated using manually transcribed data. The lowest vowel error rate (including insertions) on the defined test set is 22,72% on average over all vowels. Additionally correlation coefficients between our estimates and reference rates are calculated. These coefficients reach up to 0,796 and therefore are comparable to those for lexically-based measures (like the phone rate) on other tasks. The accuracy is sufficient to use our measurement for speaking rate adaptation.