Paper Info
Title
Incremental syntactic language models for phrase-based translation
Abstract
This paper describes a novel technique for incorporating syntactic knowledge into phrase-based machine translation through incremental syntactic parsing. Bottom-up and top-down parsers typically require a completed string as input. This requirement makes it difficult to incorporate them into phrase-based translation, which generates partial hypothesized translations from left-to-right. Incremental syntactic language models score sentences in a similar left-to-right fashion, and are therefore a good mechanism for incorporating syntax into phrase-based translation. We give a formal definition of one such lineartime syntactic language model, detail its relation to phrase-based decoding, and integrate the model with the Moses phrase-based translation system. We present empirical results on a constrained Urdu-English translation task that demonstrate a significant BLEU score improvement and a large decrease in perplexity.
Year
Venue
Keywords
2011
ACL
incremental syntactic language model,phrase-based decoding,significant bleu score improvement,incremental syntactic parsing,syntactic knowledge,phrase-based translation,lineartime syntactic language model,urdu-english translation task,moses phrase-based translation system,phrase-based machine translation,markov processes,english language,parsers,context free grammars,decoding,graphs,language model,statistical analysis,machine translation,syntax,hierarchies
Field
DocType
Volume
Noun phrase,Rule-based machine translation,Computer science,Machine translation,Phrase,Synchronous context-free grammar,Speech recognition,Phrase structure rules,Natural language processing,Artificial intelligence,Transfer-based machine translation,Computer-assisted translation
Conference
aclanthology.org
Citations 
PageRank 
References 
13
0.62
50
Authors
4
Name
Order
Citations
PageRank
Lane Schwartz120918.01
Chris Callison-Burch24872259.75
William Schuler312517.78
Stephen Wu414711.73