[PDF] Top 20 More Linguistic Annotation for Statistical Machine Translation

... Both models are trained using a very similar pipeline as for the phrase model. The main dif- ference is that the translation rules do not have to be contiguous phrases, but may contain gaps with are labeled and ... See full document

... This article describes a linguistically in- formed method for integrating phrasal verbs into statistical machine translation (SMT) systems. In a case study involving English to Bulgarian SMT, we show ... See full document

... exist quite extensive implemented formal HPSG grammars for English (Copestake and Flickinger, 2000), German (M¨uller and Kasper, 2000), and Japanese (Siegel, 2000; Siegel and Bender, 2002). HPSG is the underlying theory ... See full document

... Incorporating linguistic knowledge into statistical models is an everlasting topic in natural language ...chine translation community. Along with the suc- cess of statistical machine ... See full document

... few machine translation systems are also developed in Malayalam for translating Malayalam to English and vice versa but these are not offered to the ...Based Machine Translation (RBMT) ... See full document

... soft linguistic reordering constraints into a hierarchical phrase-based translation sys- tem: 1) a syntactic reordering model that explores reorderings for context free grammar rules; and 2) a semantic re- ... See full document

... present-day statistical ma- chine translation (SMT) have their foundation in specific assumptions about the nature of the trans- lation ...in translation theory and show that the concept of word ... See full document

... of translation quality, these translation systems have a different use case than to have a human read and ...good translation may differ significantly from what makes a successful search ... See full document

... subsequent translation into Czech is achieved using two phrase-based translation sys- ...reference) translation of the head of its English ...Czech translation. Starting with this t-Layer node ... See full document

... the translation of a phrase using the word-based translation ...literal translation of phrase constituents is often in- appropriate from a linguistic point of ...word-based translation ... See full document

... A reason why the POS rules do not shift both parts of the verb might be that the rules operate on the word level only and treat every POS tag inde- pendently of the others. A reordering model based on syntactic ... See full document

... is Statistical Machine Translation ...in machine translation between languages with significant word order differences ...Based Machine Translation (EBMT) that translates ... See full document

... More recent works include Gustavii (2005), who uses transformation-based learning to infer rules that can correct the choice of preposition made by a rule-based MT system. Her reported results show high accuracy ... See full document

... extracted linguistic features are quite com- pact, which can be learned from a small train- ing ...learned linguistic fea- tures are ...other machine translation systems, such as rule-based or ... See full document

... For English-Romanian, SMT systems are pre- sented in (Cristea, 2009) and (Ignat, 2009), with BLEU results of 0.5464 and 0.3208, respec- tively. Although both systems use as training and test data parts of the JRC-Acquis ... See full document

... The translation of a source sentence depends on other source sen- tences in the same batch with which the MaxEnt model is ...one more sentence to the batch, translations of other sentences may be- come ... See full document

... a translation model P r(e|f ) and a target language model P r(e), which can be complemented by reordering models (if the language pairs presents very long alignments in training), word penalty to avoid favoring ... See full document

... However, current BTG-based reordering meth- ods have been limited by the features used. Infor- mation might not be sufficient or representative, if only the first (or tail) words are used as features. For example, in ... See full document

... most machine translation research has focused on resource-rich settings where NMT has indeed superseded SMT, a recent line of work has managed to train an NMT system without any supervision, relying on ... See full document

... Although the interaction of these two factors can be quite profound, it may help the reader to think o f the translation probability as suggesting words from the source language t h at m[r] ... See full document