Detection of Large Segmentation Errors with Score Predictive Model

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9302)


This paper investigates a possibility of an utilization of regressive score predictive model (SPM) in a process of detection of large segmentation errors. SPM’s scores of automatically marked boundaries between all speech segments are examined and further elaborated in an effort to discover the best threshold to distinguish between small and large errors. It was shown that the suggested detection method with a proper threshold can be used to detect all large errors for a specific type of a boundary.


Detection of segmentation errors Large segmentation errors Score predictive model 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Cybernetics, Faculty of Applied SciencesUniversity of West BohemiaPilsenCzech Republic
  2. 2.New Technologies for the Information Society, Faculty of Applied SciencesUniversity of West BohemiaPilsenCzech Republic

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