Automatic labeling of phrase accents in German

Abstract

In this paper a method for the automatic labeling of phrase accents is described, based on a large text corpus that has been generated automatically and read by 100 speakers. Perception experiments on a subset of 500 utterances show a high agreement between the automatically generated accent labels and the judgment scores obtained. We computed different prosodic feature vectors from the speech signal for each syllable and trained different Gaussian distribution classifiers and artificial neural networks using the automatically generated accent labels. Recognition rates of up to 83% could be achieved for the distinction of accentuated vs. unaccentuated syllables. Similar results could be obtained for the comparison of the listeners judgments with the automatic classification.