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Statistical machine translation ( SMT) was a machine translation approach, that superseded the previous, rule-based approach because it required explicit description of each and every linguistic rule, which was costly, and which often did not generalize to other languages.
This chapter provides a gentle introduction to the field of statistical machine translation. We review the history of the field and highlight current applications of machine translation technology. Some pointers to available resources are also given.
Aug 13, 2008 · Statistical machine translation (SMT) treats the translation of natural language as a machine learning problem. By examining many samples of human-produced translation, SMT algorithms automatically learn how to translate. SMT has made tremendous strides in less than two decades, and new ideas are constantly introduced.
- Adam Lopez
- 2008
May 2, 2011 · This paper presents an overview of Statistical Machine Translation (SMT), which is currently the dominant approach in Machine Translation (MT) research.
However, an alternative approach to language translation that has been around for some time (Weaver, 1955) is called statistical machine translation (SMT). SMT is basically an application of Bayes and other probabilistic models to estimate the relative frequency with which a given phrase in the source language has been translated into the ...
Statistical Machine Translation The field of machine translation has recently been energized by the emer-gence of statistical techniques, which have brought the dream of automatic language translation closer to reality. This class-tested textbook, authored by an active researcher in the field, provides a gentle and accessible intro-
In general, statistical techniques allow automatic translation systems to be built quickly for any language-pair using only translated texts and generic software. With increasing globalization, statistical machine translation will be central to communication and commerce.
