Post-processing of automatic segmentation of speech using dynamic programming
[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee
2006
chapter in monograph / paper
english
EN Building unit-selection speech synthesisers requires a precise annotation of large speech corpora. Manual segmentation of speech is a very laborious task, hence there is the need for automatic segmentation algorithms. As it was observed that the common HMM-based method is prone to systematical errors, some boundary refinement approaches, like boundary-specific correction, were introduced. Last year, a dynamic programming fine-tuning approach was proposed, that combined two sources information, boundary error distribution and boundary MFCC statistical models. In this paper we verify the usefulness of incorporating several other data, boundary energy dynamics models and the signal periodicity information.
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