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ICASSP
2010
IEEE
13 years 4 months ago
Multiple sequence alignment based bootstrapping for improved incremental word learning
We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Irene Ayllól Clemente, Martin Heckmann, Ger...
SIGIR
1999
ACM
13 years 10 months ago
Information Retrieval Based on Context Distance and Morphology
We present an approach to information retrieval based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This conte...
Hongyan Jing, Evelyne Tzoukermann
LREC
2010
181views Education» more  LREC 2010»
13 years 7 months ago
Linguistically Motivated Unsupervised Segmentation for Machine Translation
In this paper we use statistical machine translation and morphology information from two different morphological analyzers to try to improve translation quality by linguistically ...
Mark Fishel, Harri Kirik
ACL
2008
13 years 7 months ago
Applying Morphology Generation Models to Machine Translation
We improve the quality of statistical machine translation (SMT) by applying models that predict word forms from their stems using extensive morphological and syntactic information...
Kristina Toutanova, Hisami Suzuki, Achim Ruopp
EMNLP
2007
13 years 7 months ago
Mandarin Part-of-Speech Tagging and Discriminative Reranking
We present in this paper methods to improve HMM-based part-of-speech (POS) tagging of Mandarin. We model the emission probability of an unknown word using all the characters in th...
Zhongqiang Huang, Mary P. Harper, Wen Wang