# Aesthetics of Sanskrit Poetry from the Perspective of Computational Linguistics: A Case Study Analysis on Siksastaka

arXiv: https://arxiv.org/abs/2308.07081 · HTML: https://mlsanity.com/paper/2308.07081/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 63 references that are in the map.
- First posted on arXiv 14 Aug 2023.

## Builds on (most cited first, 10 of 10)

- [Investigating Societal Biases in a Poetry Composition System](https://mlsanity.com/paper/2011.02686/) (2020)
- [SongNet: Rigid Formats Controlled Text Generation](https://mlsanity.com/paper/2004.08022/) (2020)
- [PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry](https://mlsanity.com/paper/2003.07723/) (2020)
- [Don't Go Far Off: An Empirical Study on Neural Poetry Translation](https://mlsanity.com/paper/2109.02972/) (2021)
- [Generating Major Types of Chinese Classical Poetry in a Uniformed Framework](https://mlsanity.com/paper/2003.11528/) (2020)
- [Let's FACE it. Finnish Poetry Generation with Aesthetics and Framing](https://mlsanity.com/paper/1910.13946/) (2019)
- [Acrostic Poem Generation](https://mlsanity.com/paper/2010.02239/) (2020)
- [Metrical Tagging in the Wild: Building and Annotating Poetry Corpora with Rhythmic Features](https://mlsanity.com/paper/2102.08858/) (2021)
- [Generating Classical Chinese Poems from Vernacular Chinese](https://mlsanity.com/paper/1909.00279/) (2019)
- [Chandojnanam: A Sanskrit Meter Identification and Utilization System](https://mlsanity.com/paper/2209.14924/) (2022)

## Built on by (most cited first, 2 of 2)

- [MetricalARGS: A Taxonomy for Studying Metrical Poetry with LLMs](https://mlsanity.com/paper/2510.08188/) (2025)
- [Pragya: An AI-Based Semantic Recommendation System for Sanskrit Subhasitas](https://mlsanity.com/paper/2601.06607/) (2026)

## Abstract (arXiv)

Sanskrit poetry has played a significant role in shaping the literary and cultural landscape of the Indian subcontinent for centuries. However, not much attention has been devoted to uncovering the hidden beauty of Sanskrit poetry in computational linguistics. This article explores the intersection of Sanskrit poetry and computational linguistics by proposing a roadmap of an interpretable framework to analyze and classify the qualities and characteristics of fine Sanskrit poetry. We discuss the rich tradition of Sanskrit poetry and the significance of computational linguistics in automatically identifying the characteristics of fine poetry. The proposed framework involves a human-in-the-loop approach that combines deterministic aspects delegated to machines and deep semantics left to human experts. We provide a deep analysis of Siksastaka, a Sanskrit poem, from the perspective of 6 prominent kavyashastra schools, to illustrate the proposed framework. Additionally, we provide compound, dependency, anvaya (prose order linearised form), meter, rasa (mood), alankar (figure of speech), and riti (writing style) annotations for Siksastaka and a web application to illustrate the poem's analysis and annotations. Our key contributions include the proposed framework, the analysis of Siksastaka, the annotations and the web application for future research. Link for interactive analysis: https://sanskritshala.github.io/shikshastakam/