GUJARATI POETRY CLASSIFICATION BASED ON EMOTIONS USING DEEP LEARNING

@article{Mehta2021GUJARATIPC,
  title={GUJARATI POETRY CLASSIFICATION BASED ON EMOTIONS USING DEEP LEARNING},
  author={Bhavin Mehta and Bhargav Rajyagor},
  journal={International Journal of Engineering Applied Sciences and Technology},
  year={2021}
}
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… 

Figures from this paper

References

SHOWING 1-10 OF 16 REFERENCES
Classification of Poetry Text Into the Emotional States Using Deep Learning Technique
TLDR
Experimental results depict that the proposed model outperformed the baselines studies with 88% accuracy, and the analysis of the statistical experiment also validates the performance of the proposed approach.
Towards Natural Language Processing with Figures of Speech in Hindi Poetry
TLDR
This work is the first of its kind in Hindi Natural Language Processing (NLP), which touches on the area of Hindi figure of speech and has created a systematic hierarchical structure of Hindi “Alankaar” types and sub-types and attempted and extended the work to identify a few.
Punjabi Poetry Classification: The Test of 10 Machine Learning Algorithms
TLDR
Results for Punjabi poetry classification revealed that 4 machine learning algorithms namely, Hyperpipes (HP), K- nearest neighbour (KNN), Naive Bayes (NB) and Support Vector Machine (SVM) with an accuracy of 50.63 %, 52.75 % and 58.79 % respectively, outperformed all other machinelearning algorithms under the test.
PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry
TLDR
This work conceptualizes a set of aesthetic emotions that are predictive of aesthetic appreciation in the reader, and allows the annotation of multiple labels per line to capture mixed emotions within their context, resulting in a consistent dataset for future large scale analysis.
The classification of the modern arabic poetry using machine learning
TLDR
This paper presents an approach that uses machine learning for the classification of modern Arabic poetry into four types: love poems, Islamic poems, social poems, and political poems, which is suitable for the above-mentioned classes of poems.
Stanza Type Identification using Systematization of Versification System of Hindi Poetry
TLDR
The paper covers various challenges and the best possible solutions for those challenges, describing the methodology to generate automatic metadata for “Chhand” based on the poems’ stanzas, and provides some advanced information and techniques for metadata generation for ”Muktak Chhands”.
Hindi Poetry Classification using Eager Supervised Machine Learning Algorithms
TLDR
Two eager machine learning algorithms are applied on the corpus containing 450 Hindi poems and poetry/poem gets classified based on terms present in it using a misclassification error.
Analysis of Features for Mood Detection in North Indian Classical Music - A Literature Review
Abstract – Music directly connects to the soul of living creature. It deeply influences mind and brain. Indian Classical Music is closely associated with mood and emotions. Emotion detection in
An Application of Zipf's Law for Prose and Verse Corpora Neutrality for Hindi and Marathi Languages
TLDR
Common tokens from corpora of verses and proses of Marathi as well as Hindi are identified to prove that both of them behave same as per as NLP activities are concerened and the betterment of BaSa over Zipf’s law is proved.
...
...