Making Hidden Markov Models More Transparent

نویسندگان

  • Nashira Lincoln
  • Marc Light
چکیده

Understanding the decoding algorithm for hidden Markov models is a difficult task for many students. A comprehensive understanding is difficult to gain from static state transition diagrams and tables of observation production probabilities. We have built a number of visualizations depicting a hidden Markov model for partof-speech tagging and the operation of the Viterbi algorithm. The visualizations are designed to help students grasp the operation of the HMM. In addition, we have found that the displays are useful as debugging tools for experienced researchers.

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تاریخ انتشار 2005