---
license: mit
task_categories:
- text-classification
language:
- asm
- ben
- brx
- doi
- gom
- guj
- hin
- kan
- kas
- mai
- mal
- mar
- mni
- npi
- ory
- pan
- san
- sat
- snd
- tam
- tel
- urd
- eng
tags:
- language-identification
- indian-languages
pretty_name: ILID
size_categories:
- 100K<n<1M
---

# ILID: Native Script Language Identification for Indian Languages

[**Paper**](https://huggingface.co/papers/2507.11832) | [**Code**](https://github.com/yashingle-ai/TextLangDetect) | [**Project Page**](https://yashingle-ai.github.io/ILID/)

🗣 **ILID: Indian Language Identification Dataset (23 Languages)**  
**Authors:** [Yash Ingle](mailto:yash.ingle003@gmail.com), [Dr. Pruthwik Mishra](mailto:pruthwikmishra@aid.svnit.ac.in)  
**Institute:** Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India

---

## 📄 Dataset Description

The **ILID** (Indian Language Identification Dataset) benchmark contains **250,000** sentences from **English and 22 official Indian languages**, designed for training and evaluating **language identification models**. The dataset supports the task of distinguishing between Indian languages, many of which share scripts, vocabulary, and structure.

---

## 📊 Dataset Statistics
| Language     | Code      | Train | Dev  | Test | Total  |
|--------------|-----------|-------|------|------|--------|
| Assamese     | asm       | 8000  | 1000 | 1000 | 10000  |
| Bengali      | ben       | 8000  | 1000 | 1000 | 10000  |
| Bodo         | brx       | 8000  | 1000 | 1000 | 10000  |
| Dogri        | doi       | 8000  | 1000 | 1000 | 10000  |
| Konkani      | gom       | 8000  | 1000 | 1000 | 10000  |
| Gujarati     | guj       | 8000  | 1000 | 1000 | 10000  |
| Hindi        | hin       | 8000  | 1000 | 1000 | 10000  |
| Kannada      | kan       | 8000  | 1000 | 1000 | 10000  |
| Kashmiri     | kas       | 8000  | 1000 | 1000 | 10000  |
| Maithili     | mai       | 8000  | 1000 | 1000 | 10000  |
| Malayalam    | mal       | 8000  | 1000 | 1000 | 10000  |
| Marathi      | mar       | 8000  | 1000 | 1000 | 10000  |
| Manipuri (Bengali) | mni_Beng | 8000  | 1000 | 1000 | 10000  |
| Manipuri (Meitei)  | mni_Mtei | 8000  | 1000 | 1000 | 10000  |
| Nepali       | npi       | 8000  | 1000 | 1000 | 10000  |
| Odia         | ory       | 8000  | 1000 | 1000 | 10000  |
| Punjabi      | pan       | 8000  | 1000 | 1000 | 10000  |
| Sanskrit     | san       | 8000  | 1000 | 1000 | 10000  |
| Santali      | sat       | 8000  | 1000 | 1000 | 10000  |
| Sindhi (Arabic) | snd_Arab | 8000  | 1000 | 1000 | 10000  |
| Sindhi (Devanagari) | snd_Deva | 8000  | 1000 | 1000 | 10000  |
| Tamil        | tam       | 8000  | 1000 | 1000 | 10000  |
| Telugu       | tel       | 8000  | 1000 | 1000 | 10000  |
| Urdu         | urd       | 8000  | 1000 | 1000 | 10000  |
| English      | eng       | 8000  | 1000 | 1000 | 10000  |
| **Total**    | —         | **200000** | **25000** | **25000** | **250000** |

---

## 📁 Files Provided

- `shuffled_train_sentences`: Training sentences (80% split – 200,000 samples)
- `shuffled_train_labels`: Corresponding labels for training sentences
- `shuffled_dev_sentences`: Validation (dev) sentences (10% split – 25,000 samples)
- `shuffled_dev_labels`: Corresponding labels for dev sentences
- `shuffled_test_sentences`: Test sentences (10% split – 25,000 samples)
- `shuffled_test_labels`: Corresponding labels for test sentences

## 📌 Tasks

- **Language Identification (LID)**
- **Multilingual Text Classification**
- **Benchmarking ML & DL Models on Indian Languages**

---

## 🧹 Data Collection & Cleaning

- 13 languages collected using **web scraping** from Wikipedia, news portals, and blogs.
- 10 languages sampled from **large monolingual corpora** (Bhashaverse).
- Each sentence underwent **cleaning, normalization**, and **language filtering** via FastText.

---

## 🧠 Models & Results

Baseline models include:
- **TF-IDF + Machine Learning:** SVM, Logistic Regression, Random Forest, etc.
- **FastText Classifier**
- **Fine-tuned MuRIL (BERT for Indian languages)**

Best ensemble models achieve **F1-scores of up to 0.99** on test/dev sets.

---

## 📚 Citation

If you use this dataset, please cite:

```bibtex
@misc{ingle2025ilidnativescriptlanguage,
      title={ILID: Native Script Language Identification for Indian Languages}, 
      author={Yash Ingle and Pruthwik Mishra},
      year={2025},
      eprint={2507.11832},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2507.11832}, 
}
```