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FLAIRS
2006
13 years 8 months ago
An Empirical Exploration of Hidden Markov Models: From Spelling Recognition to Speech Recognition
Hidden Markov models play a critical role in the modelling and problem solving of important AI tasks such as speech recognition and natural language processing. However, the stude...
Shieu-Hong Lin
COLING
1996
13 years 8 months ago
A Gradual Refinement Model for A Robust Thai Morphological Analyzer
This work attempts to provide a robust Thai morphological analyzer which can automatically assign the correct part-of-speech tag to the correct word with time and space efficiency...
Asanee Kawtrakul, Chalatip Thumkanon, Thitima Jamj...
NLPRS
2001
Springer
13 years 12 months ago
Automatic Segmentation of Words using Syllable Bigram Statistics
We present a syllable bigram model for segmenting a Korean sentence into words and correcting word-spacing errors in the spelling checker. We evaluated the system’s performance ...
Seung-Shik Kang, Chong-Woo Woo
LREC
2010
187views Education» more  LREC 2010»
13 years 8 months ago
A Large List of Confusion Sets for Spellchecking Assessed Against a Corpus of Real-word Errors
One of the methods that has been proposed for dealing with real-word errors (errors that occur when a correctly spelled word is substituted for the one intended) is the "conf...
Jennifer Pedler, Roger Mitton
ICDAR
2007
IEEE
14 years 1 months ago
Context-Sensitive Error Correction: Using Topic Models to Improve OCR
Modern optical character recognition software relies on human interaction to correct misrecognized characters. Even though the software often reliably identifies low-confidence ...
Michael L. Wick, Michael G. Ross, Erik G. Learned-...