Entropy Rate-based Stationary / Non-stationary Segmentation of Speech
نویسنده
چکیده
This study evaluates the potential of the entropy rate contour to identify stationary and non-stationary segments of speech signals. The segmentation produced by an entropy rate-based method is compared to the manual phoneme segmentations of the TIMIT and the KIEL corpora. Characteristic points, i.e. steepest rises and falls of the entropy rate curve and its maxima and minima are investigated to determine whether they label stationary and non-stationary speech segments. The phonetically labelled speech corpora for American English (TIMIT) and German (Kiel Corpus of Read Speech) serve as references for the corpus-based evaluation.
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