Initialization of hidden Markov models for unconstrained on-line handwriting recognition
作者： K. Nathan , A. Senior , J. Subrahmonia
DOI: 10.1109/ICASSP.1996.550783
关键词: Pattern recognition 、 Line (geometry) 、 Estimation theory 、 Covariance matrix 、 Probability distribution 、 Handwriting recognition 、 Artificial intelligence 、 Markov model 、 Computer science 、 Hidden Markov model 、 Initialization
摘要: In a hidden Markov model system, the initialization of parameters is critical to performance after retraining. This paper proposes number new approaches problem initialization, and demonstrates that method smooth alignment results in best performance.
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