Automatically Creating a Large Number of New Bilingual Dictionaries
This addresses the lack of bilingual resources for resource-poor and endangered languages, enabling broader language support in machine translation and NLP applications.
The paper tackles the problem of creating bilingual dictionaries for low-resource languages by proposing algorithms that use a single input dictionary, Wordnets, and a machine translator to generate translations, resulting in 48 new dictionaries, 30 of which are not supported by major MTs like Google and Bing.
This paper proposes approaches to automatically create a large number of new bilingual dictionaries for low-resource languages, especially resource-poor and endangered languages, from a single input bilingual dictionary. Our algorithms produce translations of words in a source language to plentiful target languages using available Wordnets and a machine translator (MT). Since our approaches rely on just one input dictionary, available Wordnets and an MT, they are applicable to any bilingual dictionary as long as one of the two languages is English or has a Wordnet linked to the Princeton Wordnet. Starting with 5 available bilingual dictionaries, we create 48 new bilingual dictionaries. Of these, 30 pairs of languages are not supported by the popular MTs: Google and Bing.