Semantic Word Embeddings For Marathi Language

Registration ID: IJNRD_183542

Published ID: IJNRD2210122

DOI: Click Here to Get

Apurv Choudhari , Ameya Ekbote , Prerona Chaudhuri

Marathi Word Embeddings, Word Vectors, CBOW, Morphological Analysis, PMI, Skip-gram, Glove

Representing words as vectors which encode their semantic properties is a vital component in natural language processing. Recent advances in distributional semantics have led to the rise of neural network-based models that use unsupervised learning to represent words as dense, distributed vectors, called word embedding. These embeddings have led to breakthroughs in performance in multiple natural language processing applications and hold the key to improving natural language processing for low-resource languages by helping machine learning algorithms learn patterns more easily from these richer representations of words, thereby allowing better generalisation from less data. In this paper, we train the CBOW model on more than 2 million Marathi sentences to create the first large-scale word embedding for the Marathi language. We analyse the quality of the learned embedding by looking at the closest neighbours to different words in the vector space and find that they capture a high degree of syntactic and semantic similarity between words. We evaluate this quantitatively by experimenting with two approaches namely training the model without using morphological analysis on the given dataset and by applying morphological analysis.

Published Paper   E-Certificate

Apurv Choudhari, Ameya Ekbote, & Prerona Chaudhuri (October-2022). Semantic Word Embeddings For Marathi Language . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(10), 994-998. https://ijnrd.org/papers/IJNRD2210122.pdf

Volume 7 Issue 10, October-2022

Pages : 994-998

Paper Reg. ID: IJNRD_183542

Published Paper Id: IJNRD2210122

Downloads: 000121993

Research Area: Computer Science & Technology 

Country: Aurangabad, MAHARASHTRA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2210122.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2210122

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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