Learning Hidden Markov Models with Hidden Markov Trees as Observation Distributions
نویسندگان
چکیده
منابع مشابه
Learning Hidden Markov Models with Hidden Markov Trees as Observation Distributions
Hidden Markov models have been found very useful for a wide range of applications in artificial intelligence. The wavelet transform arises as a new tool for signal and image analysis, with a special emphasis on nonlinearities and nonstationarities. However, learning models for wavelet coefficients have been mainly based on fixed-length sequences. We propose a novel learning architecture for seq...
متن کاملInteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial. Learning Hidden Markov Models with Hidden Markov Trees as Observation Distributions
Hidden Markov models have been found very useful for a wide range of applications in artificial intelligence. The wavelet transform arises as a new tool for signal and image analysis, with a special emphasis on nonlinearities and nonstationarities. However, learning models for wavelet coefficients have been mainly based on fixed-length sequences. We propose a novel learning architecture for seq...
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Hidden Markov models have been found very useful for a wide range of applications in machine learning and pattern recognition. The wavelet transform has emerged as a new tool for signal and image analysis. Learning models for wavelet coefficients have been mainly based on fixed-length sequences, but real applications often require to model variable-length, very long or real-time sequences. In t...
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Carl D. Mitchell 1 Mary P. Harper 2 Leah H. Jamieson 2 1AT&T Bell Laboratories, 600 Mountain Ave., Murray Hill, NJ 07974, [email protected] 2School of Electrical and Computer Engineering, Purdue University West Lafayette, IN 47907-1285, flhj,[email protected] ABSTRACT Hybrids that use a neural network to estimate the output probabilitiy for a hidden Markov model (HMM) word recognizer ha...
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ژورنال
عنوان ژورنال: INTELIGENCIA ARTIFICIAL
سال: 2008
ISSN: 1988-3064,1137-3601
DOI: 10.4114/ia.v12i37.953