Using Resource-Rich Languages to Improve Morphological Analysis of Under-Resourced Languages
Peter Baumann, Janet B. Pierrehumbert · 2014
The world-wide proliferation of digital communications has created the need for language and speech processing systems for underresourced languages.Developing such systems is challenging if only small data sets are available, and the problem is exacerbated for languages with highly productive morphology.However, many under-resourced languages are spoken in multi-lingual environments together with at least one resource-rich language and thus have numerous borrowings from resource-rich languages.Based on this insight, we argue that readily available resources from resource-rich languages can be used to bootstrap the morphological analyses of under-resourced languages with complex and productive morphological systems.In a case study of two such languages, Tagalog and Zulu, we show that an easily obtainable English wordlist can be deployed to seed a morphological analysis algorithm from a small training set of conversational transcripts.Our method achieves a precision of 100% and identifies 28 and 66 of the most productive affixes in Tagalog and Zulu, respectively.