[PDF] Top 20 Randomised Language Modelling for Statistical Machine Translation

... We conducted a range of experiments to explore the effectiveness and the error-space trade-off of Bloom filters for language modelling in SMT. The space- efficiency of these models also allows us to inves- ... See full document

... the translation model has not learned to produce the re- quired inflection of a word, or because some of the remaining violations are false ...dependency language models’ effect of improving morphological ... See full document

... natural language from a computational ...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 ... See full document

... The Statistical Machine Translation System starts with the collection of training ...some language that will take as input to the SMT ...of machine translation that will not ... See full document

... German-Czech language pair are built based on the previously proposed unsupervised MT sys- tems, with some adaptations made to accom- modate the morphologically rich characteristics of German and Czech (Tsarfaty ... See full document

... is Statistical Machine Translation ...one language to ...in machine translation between languages with significant word order differences ...Based Machine ... See full document

... syntactic language model, structured LM (SLM) (Chelba and Jelinek, 2000), that we extend to a bilingual setting and apply to SMT in Sec- tion ...syntactic language models define sentence generation ... See full document

... of language barriers must be ...automatic language translation (Machine Translation) has become an attractive area of research and ...development. Statistical Machine ... See full document

... Often more data is better data, and so it should come as no surprise that recently statistical machine trans- lation (SMT) systems have been improved by the use of large language models (LM). ... See full document

... Researchers have been trying to incorporate topic information into language models in several ways. Gildea and Hofmann (1999) use EM al- gorithm to perform a topic factor decomposition based on a segmented ... See full document

... source language by the characters of target language, although keeping the action ...of machine translation. Language Transliteration plays a significant role in various research areas ... See full document

... different language use in one and the same corpus, for instance when quoted passages differ in style from the surrounding ...target language distinguishes between different levels of formality in its forms ... See full document

... automatic translation between human ...n-gram language models, phrase-based statistical machine translation (PB- SMT) (Koehn et ...English-to-French translation and vice ... See full document

... constraints in a local context”. In our case, all the linguistic features (factors) associated with each token form a supertag to that token. Singh and Bandyopadhyay (2010) had a similar idea of incorporating linguistic ... See full document

... Table 1 shows the percent BLEU scores on the test data. The figures in the “1st pass” column show the BLEU scores in the first pass decoding when we changed the language model. The figures in the “reranking” ... See full document

... current statistical machine translation system, reordering is still a major problem for language pairs like Chinese-English, where the source and target language have significant word ... See full document

... of translation rules that have multi-level target tree annotations and discontin- uous source language ...use translation rules that have multi-level target tree annotations but require that the ... See full document

... Pivot Language methods were also used for translation dictionary induction (Schafer and Yarowsky, 2002), word sense disam- biguation (Diab and Resnik, 2002), and so ... See full document

... Recent work has shown good results using an in- coming text stream as training data for either a static or online language model (LM) in an SMT setting (Goyal et al., 2009; Levenberg and Osborne, 2009). A drawback ... See full document

... string-based language model provides as good if not better context than the deep syntax model, but only for the few words that happen to be preceded by words that are important to its lexical choice, and this ... See full document