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» Learning Rules to Improve a Machine Translation System
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ACL
2006
15 years 1 months ago
Factoring Synchronous Grammars by Sorting
Synchronous Context-Free Grammars (SCFGs) have been successfully exploited as translation models in machine translation applications. When parsing with an SCFG, computational comp...
Daniel Gildea, Giorgio Satta, Hao Zhang
EMNLP
2008
15 years 1 months ago
Predicting Success in Machine Translation
The performance of machine translation systems varies greatly depending on the source and target languages involved. Determining the contribution of different characteristics of l...
Alexandra Birch, Miles Osborne, Philipp Koehn
ACL
2007
15 years 1 months ago
Supertagged Phrase-Based Statistical Machine Translation
Until quite recently, extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic structure caused system performance to deteriorate. In this work we show that i...
Hany Hassan, Khalil Sima'an, Andy Way
LREC
2008
155views Education» more  LREC 2008»
15 years 1 months ago
Using Reordering in Statistical Machine Translation based on Alignment Block Classification
Statistical Machine Translation (SMT) is based on alignment models which learn from bilingual corpora the word correspondences between source and target language. These models are...
Marta R. Costa-Jussà, José A. R. Fon...
CHI
2009
ACM
16 years 11 days ago
Why and why not explanations improve the intelligibility of context-aware intelligent systems
Context-aware intelligent systems employ implicit inputs, and make decisions based on complex rules and machine learning models that are rarely clear to users. Such lack of system...
Brian Y. Lim, Anind K. Dey, Daniel Avrahami