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Class-based variable memory length Markov model
2005
Interspeech 2005
unpublished
In this paper, we present a class-based variable memory length Markov model and its learning algorithm. This is an extension of a variable memory length Markov model. Our model is based on a class-based probabilistic suffix tree, whose nodes have an automatically acquired wordclass relation. We experimentally compared our new model with a word-based bi-gram model, a word-based tri-gram model, a class-based bi-gram model, and a word-based variable memory length Markov model. The results show
doi:10.21437/interspeech.2005-6
fatcat:picxhlfzgfbepmnxftvanjk6zy