Publication

Abstract : Parts-of-speech tagging is a process in linguistics which deals with tagging each word in a sentence with their corresponding parts-of-speech. This process is considered to be one of the pre-processing steps for many natural language processing tasks. Earlier approaches were based on simple heuristics and later several methods were reported in the literature that incorporated machine learning techniques such as artificial neural networks. Very recently, with the advancement of deep learning-based approaches, parts-of-speech tagging process became more accurate and a reasonable number of taggers are now available for high resource languages such as English. But the low resource languages such as Malayalam is still lacking computationally efficient and accurate methods and techniques for parts-of-speech tagging. In this direction, this work proposes a deep learning-based approach for parts-of-speech tagging for the Malayalam language. Experiments conducted on real datasets show that the proposed method outperforms some of the already available methods in terms of precision and accuracy.