Unhiding Hidden Markov Models by Their Visualization (Application in Speech Processing)

  • Daniel Hajek
  • Jan Nouza
Conference paper
Part of the Eurographics book series (EUROGRAPH)


The hidden Markov model (HMM) technique has become very popular in the signal and data processing areas during the last 10 years. It is not easy, however, to understand its complex nature that is ‘hidden’ behind a ‘veil’ of two probability functions, one associated with the given space of data parameters and the other with the temporal data flow. Our system, named Visual Markov, aims at removing the veil by visualizing the continuous density HMM and displaying its individual states. Moreover, it is able to show the iterative process of HMM training, step after step. In a similar way, also the HMM based classification can be presented. The system is a highly illustrative tool that is well suited both for research and teaching purposes. In the article, we demostrate its application in the speech recognition domain.


Hide Markov Model Speech Recognition Speech Signal Speech Recognition System Viterbi Decoder 
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/Wien 1996

Authors and Affiliations

  • Daniel Hajek
    • 1
  • Jan Nouza
    • 1
  1. 1.Department of Electronics and Signal ProcessingTechnical University of LiberecLiberec 1Czech republic

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