Unsupervised training of maximum-entropy models for lexical selection in rule-based machine translation.
Francis M. TyersFelipe Sánchez-MartínezMikel L. ForcadaPublished in: EAMT (2015)
Keyphrases
- machine translation
- maximum entropy models
- natural language processing
- word sense disambiguation
- natural language
- lexical semantics
- supervised methods
- machine readable dictionaries
- cross lingual
- information extraction
- supervised learning
- language processing
- word alignment
- natural language generation
- pos tagging
- target language
- language independent
- statistical machine translation
- grammar induction
- context sensitive
- cross language information retrieval
- wordnet
- machine translation system
- semi supervised
- word level
- bilingual dictionaries
- parallel corpora
- expert systems
- chinese english
- language resources
- question answering
- multilingual documents
- machine learning
- natural language text
- english chinese
- brazilian portuguese
- lexical information
- unsupervised methods
- named entity recognition
- keywords
- information retrieval