Marco Pellin

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This paper studies feature extraction within the context of automatic speech segmentation at phonetic level. Current state-of-the-art solutions widely use cepstral features as a front-end for HMM based frameworks. Although the automatic seg-mentation results have reached the inter-annotator agreement, within a tolerance equal or higher than 20ms, the same(More)
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