GUJARATI POETRY CLASSIFICATION BASED ON EMOTIONS USING DEEP LEARNING
Poetries are the way to express the word that represents emotions and thoughts with the use of any language in the world and the computational linguistic study to the emotion recognition from poetry is an overwhelming and complex task too. Ultimate goal of this study is to disclose emotions through Gujarati poetries with the use of variety of characteristic there within Gujarati poems. Study presents a novel perspective in sentiment capture as of Gujarati Poems. ‘Kavan’ Gujarati poems collection was by hand interpreted upon the Indian idea mentioned in ‘Navarasa’. In the collection, 300+ poems were categorized into nine feeling mentioned in ‘Navarasa’, respectively ‘?????’, ‘???????’, ‘??????’, ‘? ???????’, ‘???????’, ‘????????’, ‘????????’, ‘???????’, and ‘???????’. The Zipfian allotment is part a family of related discrete power law probability distributions, which is used to identify the probability of one ‘rasa’ from the given poem.. Deep Learning has colossal set of pattern recognition tools that can be used for natural language processing and have incredible potential to locate a solution for challenging machine learning problem. Result accuracy was found up to ~87.62% of emotion classification task from Gujarati poetry corpus.