Natural Language Modeling for Phoneme-to-Text Transcription
IEEE Transactions on Pattern Analysis and Machine Intelligence
A statistical approach to machine translation
Computational Linguistics
Algorithms for finding patterns in strings
Handbook of theoretical computer science (vol. A)
Introduction to the special issue on the web as corpus
Computational Linguistics - Special issue on web as corpus
A stochastic Japanese morphological analyzer using a forward-DP backward-A* N-best search algorithm
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A spelling correction program based on a noisy channel model
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
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The noisy channel model approach is successfully applied to various natural language processing tasks. Currently the main research focus of this approach is adaptation methods, how to capture characteristics of words and expressions in a target domain given example sentences in that domain. As a solution we describe a method enlarging the vocabulary of a language model to an almost infinite size and capturing their context information. Especially the new method is suitable for languages in which words are not delimited by whitespace. We applied our method to a phoneme-to-text transcription task in Japanese and reduced about 10% of the errors in the results of an existing method.