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New Sanskrit speech corpus enables metrically accurate verse synthesis

By PulseAugur Editorial · [1 sources] ·

Researchers have developed ShlokaDhara, a new 43-hour speech corpus designed for synthesizing Sanskrit verse. This dataset addresses the limitations of existing corpora by focusing on metrical accuracy, crucial for authentic recitation governed by Chandas prosody. The corpus captures diverse meters, recitation styles, and melodic variations, enabling advancements in Text-to-Recite tasks. State-of-the-art TTS models were benchmarked, with XTTS v2 showing the highest quality, validated by Sanskrit experts and novel duration analysis metrics. AI

IMPACT Establishes a new benchmark for prosody-aware text-to-speech synthesis, potentially improving AI's ability to handle complex linguistic structures.

RANK_REASON The item is an academic paper detailing a new dataset and benchmark for a specific linguistic and computational task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Sanskrit speech corpus enables metrically accurate verse synthesis

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The item is an academic paper detailing a new dataset and benchmark for a specific linguistic and computational task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Harshal Kausadikar, Onkar Kishor Susladkar, Prathmesh Santosh Choudhari, Vedangi Deepak Deshpande, Ismini Lorentzu, Sparsh Mittal ·

    ShlokaDhara: A Multi-Speaker Sanskrit Speech Corpus for Learning Meter-Aware Prosody in Text-to-Recitation

    arXiv:2610.26929v1 Announce Type: cross Abstract: Sanskrit verse recitation is governed by $\textit{Chandas}$, a strict prosodic framework defined by rhythmic $\textit{Laghu}$ (light) and $\textit{Guru}$ (heavy) syllables. Because existing Sanskrit speech datasets prioritize ASR …

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