Machine Translation/Statistics
Statistical machine translation edit
Language models edit
Language models are used in MT for a) scoring arbitrary sequences of words (tokens) and b) given a sequence of tokens, they predict what token will likely to follow the sequence. Formally, language models are probability distributions over sequences of tokens in a given language.
N-gram models edit
Character-based models edit
Recently, it was shown that it is possible to use sub-words, characters or even bytes as basic units for language modelling[citation needed]. There are a few events focused particularly on such models and in general, processing language data on sub-word units, e.g. SCLem 2017.
Translation models edit
IBM models 1-5 edit
Phrase-based models edit
Factored translation models edit
Syntax- and tree-based models edit
Synchronous phrase grammar edit
Parallel tree-banks edit
Syntactic rules extraction edit
Decoding edit
Beam search edit
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