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.

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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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ID Code: 2981
Item Type: Conference Paper
Refereed: Yes
Keywords: Non, deterministic automata, Hidden Markov Models, lexical constraints, Automata reduction
DOI: 10.1007/b94701
ISBN: 9783540206460
ISSN: 1611-3349
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. Lecture Notes in Computer Science
Deposited On: 04 Jan 2006 00:00
Last Modified: 29 Feb 2012 12:59

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