a tutorial on hidden markov models and selected applications in speech recognition
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A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition LAWRENCE R. RABINER, FELLOW, IEEE Presented by: Chi-Chun Hsia. Markov Chain. Markov Chain. Markov Chain. It results in a Geometric Distribution. And then, what does “hidden” means?. - PowerPoint PPT PresentationTRANSCRIPT
2004/11/16 1
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
LAWRENCE R. RABINER, FELLOW, IEEEPresented by: Chi-Chun Hsia
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Markov ChainMarkov Chain
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Markov ChainMarkov Chain
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Markov ChainMarkov Chain
And then, what does “hidden” means?
It results in a Geometric Distribution
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Extension to Hidden Markov ModelExtension to Hidden Markov Model
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Extension to Hidden Markov ModelExtension to Hidden Markov Model
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Elements of an HMMElements of an HMM
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The Three Basic ProblemsThe Three Basic Problems
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Solution to Problem 1Solution to Problem 1
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Solution to Problem 1Solution to Problem 1
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Forward-Backward ProcedureForward-Backward Procedure
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Forward-Backward ProcedureForward-Backward Procedure
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Forward-Backward ProcedureForward-Backward Procedure
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Forward-Backward ProcedureForward-Backward Procedure
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Solution to Problem 2Solution to Problem 2
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Solution to Problem 2Solution to Problem 2
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Viterbi AlgorithmViterbi Algorithm
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Viterbi AlgorithmViterbi Algorithm
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Solution to Problem 3Solution to Problem 3
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Solution to Problem 3Solution to Problem 3
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EM Algorithm for HMMEM Algorithm for HMM
X.D. HUANG, Y. ARIKI, M.A. JACK
HIDDEN MARKOV MODELSFOR SPEECH RECOGNITION
EDINBURGH UNIVERSITY PRESS
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Types of HMMsTypes of HMMs
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Continuous Type HMMsContinuous Type HMMs
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Autoregressive HMMsAutoregressive HMMs
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Optimization CriterionOptimization CriterionMaximum Likelihood (ML)
Maximum Mutual Information (MMI)
Minimum Discrimination Information (MDI)
Minimum Classification Error (MCE) Chang.
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Implementation Issues for HMMsImplementation Issues for HMMs
• Scaling
• Multiple Observation Sequences
• Initial Estimates of HMM Parameters
• Effect of Insufficient Training Data
• Choice of Model
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ScalingScaling
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ScalingScaling
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ScalingScaling
And so on and on and on and on……………..
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Multiple Observation SequencesMultiple Observation Sequences
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Initial Estimates of HMM ParametersInitial Estimates of HMM Parameters
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Effect of Insufficient Training DataEffect of Insufficient Training Data
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Choice of ModelChoice of Model