Similarity and differences by finite automata

author: Tamás Gaál, Xerox Research Centre Europe, Xerox
published: Dec. 14, 2007,   recorded: October 2007,   views: 916
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Similarity and differences by finite automata in HMMs, kernels, morphological analysers, compilers and image compressors. Constraint satisfaction solving by unweighted finite automata. Weighted finite automata, basics, semirings, examples. Weighted regular expressions. Extensions: multi-tape automata, join operation, symbol classes, relations among tapes. Linguistic examples: morphology, part-of-speech tagging, German compound analysis, edit distance, asymmetric term alignment (Machine Translation with Machine Learning). Image compression and manipulation. Tools used: XFST and WFSC of Xerox.

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