ANNOTATED DISJUNCT FOR MACHINE TRANSLATION

Most information found in the Internet is available in English version. However,
most people in the world are non-English speaker. Hence, it will be of great advantage
to have reliable Machine Translation tool for those people. There are many
approaches for developing Machine Translation (MT) systems, some of them are
direct, rule-based/transfer, interlingua, and statistical approaches. This thesis focuses
on developing an MT for less resourced languages i.e. languages that do not have
available grammar formalism, parser, and corpus, such as some languages in South
East Asia. The nonexistence of bilingual corpora motivates us to use direct or transfer
approaches. Moreover, the unavailability of grammar formalism and parser in the
target languages motivates us to develop a hybrid between direct and transfer
approaches. This hybrid approach is referred as a hybrid transfer approach. This
approach uses the Annotated Disjunct (ADJ) method. This method, based on Link
Grammar (LG) formalism, can theoretically handle one-to-one, many-to-one, and
many-to-many word(s) translations. This method consists of transfer rules module
which maps source words in a source sentence (SS) into target words in correct
position in a target sentence (TS). The developed transfer rules are demonstrated on
English → Indonesian translation tasks. An experimental evaluation is conducted to
measure the performance of the developed system over available English-Indonesian
MT systems. The developed ADJ-based MT system translated simple, compound, and
complex English sentences in present, present continuous, present perfect, past, past
perfect, and future tenses with better precision than other systems, with the accuracy
of 71.17% in Subjective Sentence Error Rate metric.