Unsupervised morphological parsing of Bengali

Unsupervised morphological analysis is the task of segmenting words into prefixes, suffixes and stems without prior knowledge of language-specific morphotactics and morpho-phonological rules. This paper introduces a simple, yet highly effective algorithm for unsupervised morphological learning for Bengali, an Indo-Aryan language that is highly inflectional in nature. When evaluated on a set of 4110 humansegmented Bengali words, our algorithm achieves an F-score of 83%, substantially outperforming Linguistica, one of the most widely-used unsupervised morphological parsers, by about 23%. Response to Reviewers: We have added reviewers' comments as an attachment to the manuscript. Unsupervised Morphological Parsing of Bengali Sajib Dasgupta and Vincent Ng ({sajib,vince}@hlt.utdallas.edu) Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX 75083, USA Abstract. Unsupervised morphological analysis is the task of segmenting words into prefixes, Unsupervised morphological analysis is the task of segmenting words into prefixes, suffixes and stems without prior knowledge of language-specific morphotactics and morphophonological rules. This paper introduces a simple, yet highly effective algorithm for unsupervised morphological learning for Bengali, an Indo-Aryan language that is highly inflectional in nature. When evaluated on a set of 4110 human-segmented Bengali words, our algorithm achieves an F-score of 83%, substantially outperforming Linguistica, one of the most widelyused unsupervised morphological parsers, by about 23%.