A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
Rabiner, 1989, A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition (Proceedings of the IEEE)
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2 cards in “IV.C Variants on HMM structures” · whole deck
IV.C Variants on HMM structures
- What are null transitions?Transitions that produce no observation (in arc-emitting HMMs like IBM’s). They allow skipping states, compactly encode alternative pronunciations (deletions) in word networks, and let a digit grammar loop back to produce digit strings of any length.
- Rabiner, 1989, A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition (Proceedings of the IEEE), IV.C Variants on HMM structures
- What is parameter tying, and when is it useful?Setting up an equivalence between parameters of different states (e.g. the same observation density for several states), which reduces the number of independent parameters; especially useful when training data is insufficient.
- Rabiner, 1989, A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition (Proceedings of the IEEE), IV.C Variants on HMM structures
Source
- Lawrence R. Rabiner. 1989. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. In Proceedings of the IEEE, pp. 257–286. doi:10.1109/5.18626