IBM alignment models: Difference between revisions

Revision as of 05:23, 28 October 2015

Revision as of 03:13, 25 February 2016

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IBM Model 1 is weak in terms of conducting reordering or adding and dropping words. In most cases, words that follow each other in one language would have a different order after translation, but IBM Model 1 treats all kinds of reordering as equally possible.

Another problem while aligning is the fertility (the notion that input words would produce a specific number of output words after translation). In most cases one input word will be translated into one single word, but some words will produce multiple words or even get dropped (produce noneno words at all). The fertility of word models addresses this aspect of translation. While adding additional components increases the complexity of models, the main principles of IBM Model 1 are constant.<ref>{{cite journal | last1 = Wołk | first1 = K. | last2 = Marasek | first2 = K. | title = Real-Time Statistical Speech Translation | url = | journal = Advances in Intelligent Systems and Computing | publisher = Springer | volume = 275 | pages = 107–114 | issn = 2194-5357 | isbn = 978-3-319-05950-1}}</ref>

== Model 2 ==