A comparison of HMM, Naïve Bayesian, and Markov model in exploiting knowledge content in digital ink: A case study on handwritten music notation recognition

@article{Lee2010ACO,
  title={A comparison of HMM, Na{\"i}ve Bayesian, and Markov model in exploiting knowledge content in digital ink: A case study on handwritten music notation recognition},
  author={Kian Chin Lee and Somnuk Phon-Amnuaisuk and Choo-Yee Ting},
  journal={2010 IEEE International Conference on Multimedia and Expo},
  year={2010},
  pages={292-297}
}
The performance of a model is dependent not only on the amount of knowledge available to the model but also on how the knowledge is exploited. We investigate the recognition of handwritten musical notation based on three related probabilistic inference techniques: Hidden Markov Models (HMMs), Markov Models (MMs) and Naïve Bayes (NBs). Music notes are written on a tablet. A sequence of ink patterns representing this symbol is captured and subsequently employed for constructing the models of HMMs… CONTINUE READING
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