L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Library
Despite being the third most popular language in India, the Marathi language lacks useful NLP resources. Moreover, popular NLP libraries do not have support for the Marathi language. With L3Cube-MahaNLP, we aim to build resources and a library for Marathi natural language processing. We present datasets and transformer models for supervised tasks like sentiment analysis, named entity recognition, and hate speech detection. We have also published a monolingual Marathi corpus for unsupervised language modeling tasks. Overall we present MahaCorpus, MahaSent, MahaNER, and MahaHate datasets and their corresponding MahaBERT models fine-tuned on these datasets. We aim to move ahead of benchmark datasets and prepare useful resources for Marathi. The resources are available at https://github.com/l3cube-pune/MarathiNLP.
Code (1)
Tasks
Hate Speech DetectionLanguage ModelingLanguage Modellingnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Sentiment AnalysisSimilar Papers 제목 키워드 기반
mahaNLP: A Marathi Natural Language Processing Library
We present mahaNLP, an open-source natural language processing (NLP) library specifically built for the Marathi language. It aims to enhance the support for the low-resource Indian language Marathi in the field of NLP. I…
Hate Speech DetectionNERSentenceSentence Completion+1Curating Stopwords in Marathi: A TF-IDF Approach for Improved Text Analysis and Information Retrieval
Stopwords are commonly used words in a language that are often considered to be of little value in determining the meaning or significance of a document. These words occur frequently in most texts and don't provide much …
Information RetrievalRetrievalSentiment Analysistext-classification+1MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models
Paraphrases are a vital tool to assist language understanding tasks such as question answering, style transfer, semantic parsing, and data augmentation tasks. Indic languages are complex in natural language processing (N…
Question AnsweringData AugmentationSemantic ParsingStyle TransferL3Cube-MahaSum: A Comprehensive Dataset and BART Models for Abstractive Text Summarization in Marathi
We present the MahaSUM dataset, a large-scale collection of diverse news articles in Marathi, designed to facilitate the training and evaluation of models for abstractive summarization tasks in Indic languages. The datas…
Abstractive Text SummarizationArticlesText SummarizationL3CubeMahaSent: A Marathi Tweet-based Sentiment Analysis Dataset
Sentiment analysis is one of the most fundamental tasks in Natural Language Processing. Popular languages like English, Arabic, Russian, Mandarin, and also Indian languages such as Hindi, Bengali, Tamil have seen a signi…
Sentiment Analysis