Abstract
Reduplication is a productive morphological process widely used in a substantial number of languages in the world. Reduplication is a well-studied phenomenon, and several typological works have provided evidence for different types of reduplication in most of the languages around the world. Addressing reduplication plays a vital role in the efficiency of POS tagger, sentiment analysis, as well as other NLP tasks. However, it is an understudied area in computational linguistics, especially in low-resource languages like Assamese. This article first describes different types of reduplication and their shapes that occur in Assamese. Second, an exhaustive set of reduplication formation rules is compiled that is incorporated to build a system to identify reduplication in Assamese text. The results of the experiments performed on three different domain datasets showed that the rule-based system can identify reduplicated expressions with an average precision, recall, and F1 scores of 94.19%, 98.07%, and 96.07%, respectively. Third, it is shown that the Assamese reduplication processes can be captured through a two-way finite-state transducer (2-way FST). Finally, two broad categories of reduplicative processes along with their corresponding 2-way FST model are presented.
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