AH-Translit-Bench 2.0.0

Arabic to Hindi transliteration benchmark dataset (2k per domain)

AH-Translit_Benchmark

Arabic → Hindi Transliteration Benchmark Dataset

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Description

AH-Translit_Bench is a 6,000-sample Arabic-to-Hindi transliteration benchmark dataset, curated for systematic evaluation and comparison of transliteration models across three linguistically distinct domains:

• Quranic Arabic
• Modern Standard Arabic (Daily Use)
• Modern Standard Arabic (Bibliographic)

Each domain contributes 2,000 carefully selected sentence pairs, ensuring balanced, fair, and domain-aware evaluation of cross-script transliteration systems.

This benchmark is designed strictly for testing and reporting results, and is complementary to the full AH-Translit training dataset.

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Dataset Curators

Vilal Ali MS by Research, Data Sciences and Analytics Centre IIIT Hyderabad 📧 [e-mail]

Mohd Hozaifa Khan MS by Research, CVIT IIIT Hyderabad 📧 [e-mail]

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Dataset Usage

Designed for benchmarking and evaluating Arabic-to-Hindi phonetic transliteration models under domain shifts and varying sequence-length conditions.

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Content Type

Text — sentence-level Arabic source text paired with Hindi (Devanagari) phonetic transliteration.

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File Type

CSV (Comma-Separated Values)

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Dataset Structure

AH-Translit-Benchmark-Dataset
├── quranic_benchmark_2000.csv
├── msa_dailyuse_benchmark_2000.csv
├── msa_bibliographic_benchmark_2000.csv
├── all_domain_mix_benchmark_6000.csv
└── README.md

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File Descriptions

• quranic_benchmark_2000.csv 2,000 sentence pairs from Quranic Arabic, characterized by long sequences and rich morphology.

• msa_dailyuse_benchmark_2000.csv 2,000 sentence pairs from daily-use Modern Standard Arabic, representing short and conversational inputs.

• msa_bibliographic_benchmark_2000.csv 2,000 sentence pairs from formal and bibliographic MSA, featuring higher lexical diversity.

• all_domain_mix_benchmark_6000.csv Combined benchmark file containing all 6,000 samples, evenly distributed across domains.

Each CSV contains exactly two columns:

Arabic , Hindi

Hindi text is phonetic transliteration, not translation.

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Benchmark Scale Summary

Domain	Samples
Quranic	2,000
MSA Daily Use	2,000
MSA Bibliographic	2,000
Total	6,000

This strict balance ensures macro-averaged, unbiased evaluation across domains.

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How to Use This Dataset

Load a Benchmark CSV

import pandas as pd

df = pd.read_csv("quranic_benchmark_2000.csv")
print(df.head())
print(df.shape)  # (2000, 2)

Load the Full Benchmark Mix

df_all = pd.read_csv("all_domain_mix_benchmark_6000.csv")
print(df_all.shape)  # (6000, 2)

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🧾 Example Data Snippet

Arabic,Hindi
المطبعة الحيدرية،,"अल-मतबअह अल-हैदरियह,"

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Version Overview

Version 2.0 (Current)

Version Description: Expanded benchmark release with 2,000 samples per domain, covering Quranic Arabic, MSA Daily Use, and MSA Bibliographic text, along with a combined 6,000-sample mixed-domain benchmark file for standardized evaluation.

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Important Notes

• This is a benchmark-only dataset
• Not intended for model training
• No overlap with AH-Translit training splits
• Focuses on phonetic fidelity, not semantic translation

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License

• Code: MIT License
• Dataset: Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0)

Permitted for research and educational use only with proper attribution.

Full license: https://creativecommons.org/licenses/by-nc/4.0/

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Acknowledgements

The AH-Translit team at IIIT Hyderabad thanks India Data for hosting and supporting this benchmark dataset.

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Authors

Vilal Ali

Mohd Hozaifa Khan