Reduction of Non Deterministic Automata for Hidden Markov Model Based Pattern Recognition Applications
Maire, Frederic D., Wathne, Frank, & Lifchitz, Alain (2003) Reduction of Non Deterministic Automata for Hidden Markov Model Based Pattern Recognition Applications. In AI 2003: Advances in Artificial Intelligence: 16th Australian Conference on AI, Springer, Perth, Australia, pp. 466-476.
Most on-line cursive handwriting recognition systems use a lexical constraint to help improve the recognition performance. Traditionally, the vocabulary lexicon is stored in a trie (automaton whose underlying graph is a tree). In a previous paper, we showed that non-deterministic automata were computationally more efficient than tries. In this paper, we propose a new method for constructing incrementally small non-deterministic automata from lexicons. We present experimental results demonstrating a significant reduction in the number of labels in the automata. This reduction yields a proportional speed-up in HMM based lexically constrained pattern recognition systems.
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|Item Type:||Conference Paper|
|Keywords:||Non, deterministic automata, Hidden Markov Models, lexical constraints, Automata reduction|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2003 Springer|
|Copyright Statement:||This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springer.de/comp/lncs/ Lecture Notes in Computer Science|
|Deposited On:||04 Jan 2006|
|Last Modified:||29 Feb 2012 22:59|
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