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Datasets:
sanganaka
/
Vedavani-Dataset

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Languages:
Sanskrit
ArXiv:
Tags:
automatic-speech-recognition
speech
sanskrit
vedic
low-resource
whisper
License:
Dataset card Files
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  ---
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ pretty_name: Vedavani
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+ tags:
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+ - automatic-speech-recognition
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+ - speech
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+ - sanskrit
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+ - vedic
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+ - low-resource
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+ - whisper
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+ - audio
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+ language:
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+ - sa
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  license: apache-2.0
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+ task_categories:
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+ - automatic-speech-recognition
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+ multilinguality: monolingual
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+ annotations_creators:
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+ - expert-generated
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+ source_datasets: []
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+ paper: https://arxiv.org/pdf/2506.00145v1
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+ dataset_info:
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+ features:
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+ - name: audio
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+ dtype: audio
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+ - name: transcription
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_examples: 24623
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+ - name: validation
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+ num_examples: 3078
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+ - name: test
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+ num_examples: 3078
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+ download_size: ~5.4GB
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+ dataset_size: ~
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  ---
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+
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+ # Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry
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+
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+ **Vedavani** is the first benchmark dataset for **automatic speech recognition (ASR)** on **Vedic Sanskrit poetry**, consisting of richly annotated verses from the *Rig Veda* and *Atharva Veda*. This corpus captures the unique **prosodic structure**, **phonetic complexity**, and **chanting style** found in traditional Vedic recitation.
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+
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+ 🔗 **Paper**: [Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry (ACL 2025)](https://arxiv.org/pdf/2506.00145v1)
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+ 📁 **GitHub Repository**: [https://github.com/SujeetNlp/Vedavani](https://github.com/SujeetNlp/Vedavani)
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+ 📜 **License**: Apache License 2.0
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+
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+
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+ ---
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+
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+ ## 📦 Dataset Contents
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+
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+ This repository contains:
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+
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+ - `train.csv` — Metadata for training set
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+ - `validation.csv` — Metadata for validation set
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+ - `test.csv` — Metadata for test set
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+ - `Audio_files` — Audio files in WAV format (segmented and aligned) [Due to hugging face restrictions files are organized in folder containing maximum 9000 files each. While using them in training/testing kindly move all the files in one single directory.]
57
+ - `README` — Textual documentation
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+
59
+ Each CSV includes:
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+ - `path`: Relative path to audio file
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+ - `transcription`: Ground-truth text in **Devanagari script**, including **prosodic markers**
62
+
63
+ ---
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+
65
+ ## 📊 Dataset Statistics
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+
67
+ | Property | Value |
68
+ |----------------------|--------------------------|
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+ | Total Duration | ~54 hours |
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+ | Total Samples | 30,779 |
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+ | Verses from Rig Veda | 20,782 |
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+ | Verses from Atharva Veda | 9,997 |
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+ | Avg. Audio Length | 6.36 seconds |
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+ | Vocabulary Size | 64,082 unique words |
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+
76
+ ### Data Splits
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+
78
+ | Split | # Samples |
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+ |------------|-----------|
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+ | Train | 24,623 |
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+ | Validation | 3,078 |
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+ | Test | 3,078 |
83
+
84
+ ---
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+
86
+ ## Use Cases
87
+
88
+ Vedavani is particularly useful for:
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+
90
+ - Fine-tuning and benchmarking ASR models (e.g., Whisper, IndicWhisper, Wav2Vec2)
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+ - Studying phonetic alignment in Sanskrit poetry
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+ - Low-resource speech processing
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+ - Prosody-aware speech models
94
+
95
+ ---
96
+
97
+
98
+ # Citation
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+ ```bibtex
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+ @article{
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+ title={Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry},
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+ author={Sujeet Kumar, Pretam Ray, Abhinay Beerukuri, Shrey Kamoji, Manoj Balaji Jagadeeshan, and Pawan Goyal},
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+ journal={https://arxiv.org/pdf/2506.00145v1},
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+ year={2025}
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+ }
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+ ```
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