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» Lexicalized Hidden Markov Models for Part-of-Speech Tagging
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GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
13 years 10 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
COLING
2008
13 years 6 months ago
Weakly Supervised Supertagging with Grammar-Informed Initialization
Much previous work has investigated weak supervision with HMMs and tag dictionaries for part-of-speech tagging, but there have been no similar investigations for the harder proble...
Jason Baldridge
EMNLP
2010
13 years 3 months ago
Crouching Dirichlet, Hidden Markov Model: Unsupervised POS Tagging with Context Local Tag Generation
We define the crouching Dirichlet, hidden Markov model (CDHMM), an HMM for partof-speech tagging which draws state prior distributions for each local document context. This simple...
Taesun Moon, Katrin Erk, Jason Baldridge
INTERSPEECH
2010
13 years 2 days ago
Hidden Markov models with context-sensitive observations for grapheme-to-phoneme conversion
Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...
NLPRS
2001
Springer
13 years 9 months ago
A Maximum Entropy Tagger with Unsupervised Hidden Markov Models
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
Jun'ichi Kazama, Yusuke Miyao, Jun-ichi Tsujii