mahendraphd/Indic_Hindi-English_Parallel_Speech

Dataset Access Information

This dataset is provided for research and academic purposes. Access to the dataset is gated, and users must request permission before downloading.

Dataset Summary

This repository contains the Hindi–English Speech-to-Speech Translation (S2ST) dataset introduced in the paper:

Benchmarking Hindi-to-English Direct Speech-to-Speech Translation with Synthetic Data

The dataset is designed to support research on direct speech-to-speech translation (S2ST) for the low-resource language pair Hindi → English. The dataset consists of parallel speech pairs and their transcripts, where:

English speech is natural speech collected from TED Talks.

Hindi speech is synthesized from translated Hindi text using a TTS system.

Dataset Structure

The dataset is divided into three splits:

• train
• dev
• test

Each split is provided as a compressed .zip file:

Train Set

train/
├── en/                   #english audio directory
├── hi/                   #hindi audio directory
└── train.tsv             #transcripts file

Dev Set

dev/
├── en/                   #english audio directory
├── hi/                   #hindi audio directory
└── dev.tsv               #transcripts file

Test Set

test/
├── en/                   #english audio directory
├── hi/                   #hindi audio directory
└── test.tsv              #transcripts file

Transcript file structure

hi_audio	    en_audio	    hi_text  	       en_text
hi/000001.wav	en/000001.wav	हिंदी वाक्य            English sentence
hi/000002.wav	en/000002.wav	हिंदी वाक्य            English sentence

To download the dataset, clone the repo and extract

git clone https://huggingface.co/datasets/mahendraphd/Indic_Hindi-English_Parallel_Speech
cd Indic_Hindi-English_Parallel_Speech

Loading the Dataset in Python

The dataset can be loaded directly from Hugging Face using the datasets library.

from datasets import load_dataset

dataset = load_dataset("mahendraphd/Indic_Hindi-English_Parallel_Speech")

print(dataset)

Citation

If you use this dataset in your research or applications, please cite the Indic_Hi_En_S2ST:

@article{gupta2025_Indic_Hi_En_S2ST,
  title={Benchmarking Hindi-to-English Direct Speech-to-Speech Translation with Synthetic Data},
  author={Gupta, Mahendra and Dutta, Maitreyee and Maurya, Chandresh Kumar},
  journal={Language Resources and Evaluation},
  year={2025},
  publisher={Springer},
  doi={10.1007/s10579-025-09827-2}
}