Normalization of Numeronyms using NLP Techniques

This paper presents a method to apply Natural Language Processing for normalizing numeronyms to make them understandable by humans. We try to deal with the problem using two approaches, viz., semi-supervised approach and supervised approach. For the semi-supervised approach, we make use of the state of the art DamerauLevenshtein distance of words. We then apply Cosine Similarity for selection of the normalized text and reach greater accuracy in solving the problem. For the supervised approach, we used a deep learning architecture to solve the problem at hand. Our approach garners accuracy figures of 71% and 72% for Bengali and English (for the semi-supervised approach) and 89% for the supervised approach, respectively.