Machine Translation History of Machine Translation Difficulties in Machine Translation Structure of Machine Translation System Research methods for Machine Translation

History of Machine Translation Early 1950s –Infancy time for Machine Translation –Research was modest constrained by the limitations of hardware, esp. memories and slow access to storage –A large number of projects supported by US agencies

History of MT (cont.) At the end of 1950s –A bad time for Machine Translation –Some promise before had remained unrealized –The number of lab working in the field was sharply reduced all over the world –Few of them were able to obtain funding for more long-range research programs

History of MT (cont.) A resurgence in the 1980s –Many of the efforts were rapidly deemed successfully –The most conspicuous example was the METEO system, developed at U. of Montreal –METEO provided the French translations of weather reports used by airline, shipping companies and others

Difficulties in MT Some typical factors contribute to the difficulty –Words with multiple meanings –Sentences with multiple grammatical structures –Uncertainty about what a pronoun refers –Other problems of grammar

Difficulties in MT (cont.) Two common misunderstandings make translation seem simpler than it is –Translation is not primarily a linguistic operation –Translation is not an operation that preserves meaning –Examples later

Difficulties in MT (cont.) Example for the first misunderstanding –“The police refused the students a permit because they feared violence.” –It is to be translated in to French –“police” is feminine, “they” will also have to be feminine. –Replace the word “feared”with “advocated” –“they” refer to “students” and is masculine now

Difficulties in MT (cont.) For the second misunderstanding –Different languages have different usage, for example: there are languages like French in which pronouns must show number and gender, Japanese where pronouns are often omitted altogether, Russian where there are no articles, Chinese where nouns do not differentiate singular and plural nor verbs present and past

Structure of MT Systems Generally they all have lexical, morphological, syntactic and semantic components, one for each of the two languages, for treating basic words, complex words, sentences and meanings

Structure of MT Systems (cont.) “transfer” component: the only one that is specialized for a particular pair of languages, which converts the most abstract source representation that can be achieved into a corresponding abstract target representation

Structure of MT Systems (cont.) Some systems make use of a so-called “interlingua” or intermediate language –The transfer stage is divided into two steps, one translating a source sentence into the interlingua and the other translating the result of this into an abstract representation in the target language

Research methods of MT 1950s and 1960s –Information theory, categorial grammar, transformational-generative grammar, dependency grammar 1970s and 1980s –Artificial intelligence, non-linguistic knowledge bases, semantics and interlingua-based system

Research methods of MT (cont.) 1990s –Neural networks, connectionism, parallel processing and statistical methods In the future –MT research will be oriented towards the development of ‘translation modules’ to be integrated in general ‘office’ systems, rather than the design of systems to be self-contained and independent