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Natural Language Processing based Text Imputation for Malayalam Corpora

机译:基于自然语言处理的马拉雅拉语语料库的文本插补

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摘要

The prediction task in Natural Language Processing intends to figure out the missing characters, letter, word, expression, or sentence that conceivable follows in a given fragment of a book. Since the beginning of NLP, numerous frameworks with various techniques were produced for various dialects. The missing content prediction is one among the significant concerns of Natural Language Processing. Moreover, most of the text prediction related tasks are conducted in different dialects but not in Malayalam. Over these years though having some of the best classics, historical records and many more to keep the world interested with, the Malayalam was lacking many of the advantages that any other language process in the digital world. This is because there are only a few standard models that could fit into the Malayalam. In this paper, an attempt is made to fit the BERT into Malayalam. A Malayalam pre-trained model will be creating and implementing some of its applications with the model and discussing its scope and areas of development to be addressed and future research scope.
机译:自然语言处理中的预测任务旨在找出在给定书本片段中可能出现的缺少的字符,字母,单词,表达方式或句子。自从NLP诞生以来,针对各种方言产生了具有各种技术的众多框架。缺少内容的预测是自然语言处理的重要关注之一。此外,大多数与文本预测相关的任务都是在不同的方言中进行的,而在马拉雅拉姆语中则没有。这些年来,尽管马拉雅拉姆语有一些最好的经典,历史记录以及许多让世界感兴趣的东西,但它却缺乏数字世界中任何其他语言所具有的许多优势。这是因为只有少数标准模型可以放入马拉雅拉姆语中。在本文中,尝试将BERT装入马拉雅拉姆语。马拉雅拉姆语预训练的模型将使用该模型来创建和实现其某些应用程序,并讨论其要解决的范围和发展领域以及未来的研究范围。

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