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2003
Springer

Reduction of Non Deterministic Automata for Hidden Markov Model Based Pattern Recognition Applications

10 years 6 months ago
Reduction of Non Deterministic Automata for Hidden Markov Model Based Pattern Recognition Applications
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.
Frédéric Maire, Frank Wathne, Alain
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where AUSAI
Authors Frédéric Maire, Frank Wathne, Alain Lifchitz
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