Abstract:
Machine Translation (MT) refers to the use of computers for the task of translating automat
ically from one language to another. The differences between languages and especially the
inherent ambiguity of language make MT a very difficult problem. Traditional approaches to
MT have relied on humans supplying linguistic knowledge in the form of rules to transform
text in one language to another. Given the vastness of language, this is a highly knowledge
intensive task. Statistical MT is a radically different approach that automatically acquires
knowledge from large amounts of training data. This knowledge, which is typically in the
form of probabilities of various language features, is used to guide the translation process.
This report provides an overview of MT techniques, and looks in detail at the basic statisti
cal model.
