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GSoC'11: Rule-based finite-state disambiguation

Mitchell JEFFREY Monash University, Melbourne, Australia (UTC+10) IRC: mitch-j on #apertium

Introduction Machine learning facilitates international communication, and is especially useful in supporting the continued usage of minority languages for which human translators are in short supply. Apertium represents both an academic exercise and a useful software development project whose goal it is to provide an accurate, universal automated translation engine and accompanying language-specific datasets.

My bilingual experience has taught me that each language provides an insightful, valuable and most importantly, unique way of interpreting and conceptualising the world around us. The subtle tools of expression encapsulated within a language are extremely valuable both in terms of cultural heritage and linguistic history. A sad fact of the modern world is that less frequently spoken minority languages are slowly dying off in response to the convenience and necessity required by increasingly globalised communication. Language extinction is occurring all around the world, including my native Australia which once boasted almost 1000 indigenous languages.

Machine translation is one tool of many which could help slow the decline of minority languages not only as a stand-in replacement for human translators, but also as a educational tool. Being an open source project, Apertium is in a position to support minority languages which aren’t financially viable to maintain in the commercial sense.

On a personal level, machine translation projects such as this represent a unique opportunity to combine my interests in computer science, natural language and mathematics/logic. I am interested in how humans communicate and convey meaning; investigating how machines could process human language (for instance with a translation package such as Apertium) would not only be an insightful venture in itself, but would also inform my understanding of the condition of human communication.

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