| ---
|
| pretty_name: Vedavani
|
| tags:
|
| - automatic-speech-recognition
|
| - speech
|
| - sanskrit
|
| - vedic
|
| - low-resource
|
| - whisper
|
| - audio
|
| language:
|
| - sa
|
| license: apache-2.0
|
| task_categories:
|
| - automatic-speech-recognition
|
| multilinguality: monolingual
|
| annotations_creators:
|
| - expert-generated
|
| source_datasets: []
|
| paper: https://arxiv.org/pdf/2506.00145v1
|
| dataset_info:
|
| features:
|
| - name: audio
|
| dtype: audio
|
| - name: transcription
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_examples: 24623
|
| - name: validation
|
| num_examples: 3078
|
| - name: test
|
| num_examples: 3078
|
| download_size: ~5.4GB
|
| dataset_size: ~
|
| ---
|
|
|
| # Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry
|
|
|
| **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.
|
|
|
| 🔗 **Paper**: [Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry (ACL 2025)](https://arxiv.org/pdf/2506.00145v1)
|
| 📁 **GitHub Repository**: [https://github.com/SujeetNlp/Vedavani](https://github.com/SujeetNlp/Vedavani)
|
| 📜 **License**: Apache License 2.0
|
|
|
|
|
| ---
|
|
|
| ## 📦 Dataset Contents
|
|
|
| This repository contains:
|
|
|
| - `train.csv` — Metadata for training set
|
| - `validation.csv` — Metadata for validation set
|
| - `test.csv` — Metadata for test set
|
| - `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.]
|
| - `README` — Textual documentation
|
|
|
| Each CSV includes:
|
| - `path`: Relative path to audio file
|
| - `transcription`: Ground-truth text in **Devanagari script**, including **prosodic markers**
|
|
|
| ---
|
|
|
| ## 📊 Dataset Statistics
|
|
|
| | Property | Value |
|
| |----------------------|--------------------------|
|
| | Total Duration | ~54 hours |
|
| | Total Samples | 30,779 |
|
| | Verses from Rig Veda | 20,782 |
|
| | Verses from Atharva Veda | 9,997 |
|
| | Avg. Audio Length | 6.36 seconds |
|
| | Vocabulary Size | 64,082 unique words |
|
|
|
| ### Data Splits
|
|
|
| | Split | # Samples |
|
| |------------|-----------|
|
| | Train | 24,623 |
|
| | Validation | 3,078 |
|
| | Test | 3,078 |
|
|
|
| ---
|
|
|
| ## Use Cases
|
|
|
| Vedavani is particularly useful for:
|
|
|
| - Fine-tuning and benchmarking ASR models (e.g., Whisper, IndicWhisper, Wav2Vec2)
|
| - Studying phonetic alignment in Sanskrit poetry
|
| - Low-resource speech processing
|
| - Prosody-aware speech models
|
|
|
| ---
|
|
|
|
|
| # Citation
|
| ```bibtex
|
| @article{
|
| title={Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry},
|
| author={Sujeet Kumar, Pretam Ray, Abhinay Beerukuri, Shrey Kamoji, Manoj Balaji Jagadeeshan, and Pawan Goyal},
|
| journal={https://arxiv.org/pdf/2506.00145v1},
|
| year={2025}
|
| }
|
| ```
|
|
|
