On the Processing of Fuzzy Patterns for Text Independent Phonetic Speech Segmentation

  • Luis D. Huerta-Hernández
  • Carlos A. Reyes-García
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)


In this work we propose an algorithm for continuous speech segmentation with text independency. In our approach we do not use feature vectors in order to detect phoneme boundaries, instead we only make use of the intensity measure. Obtaining with this a remarkable reduction in the amount of information needed and simplified rules on the processing. In the process only a pre-emphasis filter, and one strategy based on a distance measure with normalized fuzzy memberships over the signal patterns are used. In the preliminary results the method reaches up to 77.54% of correct segmentation with a 20 msec. accuracy and an over segmentation rate near to 0%. The algorithm implementation, the experiments, as well as some results are shown.


Speech Recognition Speech Signal Fuzzy Membership Automatic Speech Recognition Frame Size 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Luis D. Huerta-Hernández
    • 1
    • 2
  • Carlos A. Reyes-García
    • 1
  1. 1.Instituto Nacional de Astrofísica Óptica y Electrónica (INAOE)PueblaMéxico
  2. 2.Instituto Tecnológico Superior de Acatlán de OsorioUnidad Tecnológica, Acatlán de OsorioPueblaMéxico

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