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---
license: cc-by-sa-4.0
task_categories:
- text-classification
- text2text-generation
language:
- hi
- en
- mr
- pa
- ne
- sd
- as
- gu
- ta
- te
- ur
- or
tags:
- multilingual
- language-identification
- text-classification
- indian
pretty_name: Language Identification Dataset
size_categories:
- 100K<n<1M
---
# Dataset Card for Language Identification Dataset
### Dataset Description
- **Repository:** processvenue/language_identification
- **Total Samples:** 135784
- **Number of Languages:** 18
- **Splits:**
- Train: 95048 samples
- Validation: 20367 samples
- Test: 20369 samples
### Sample Notebook:
https://www.kaggle.com/code/rishabhbhartiya/indian-language-classification-smote-resampled
### Kaggle Dataset link:
https://www.kaggle.com/datasets/processvenue/indian-language-identification
### Dataset Summary
A comprehensive dataset for Indian language identification and text classification. The dataset contains text samples across 18 major Indian languages, making it suitable for developing language identification systems and multilingual NLP applications.
### Languages and Distribution
```
Language Distribution:
1. Punjabi 15075
2. Odia 14258
3. Konkani 14098
4. Hindi 13469
5. Sanskrit 11788
6. Bengali 10036
7. English 9819
8. Sindhi 8838
9. Nepali 8694
10. Marathi 6625
11. Gujarati 3788
12. Telugu 3563
13. Malayalam 3423
14. Tamil 3195
15. Kannada 2651
16. Kashmiri 2282
17. Urdu 2272
18. Assamese 1910
```
### Data Fields
- `Headline`: The input text sample
- `Language`: The language label (one of the 18 languages listed above)
### Usage Example
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("Process-Venue/Language-Identification-v2")
# Access splits
train_data = dataset['train']
validation_data = dataset['validation']
test_data = dataset['test']
# Example usage
print(f"Sample text: {train_data[0]['Headline']}")
print(f"Language: {train_data[0]['Language']}")
```
### Applications
1. **Language Identification Systems**
- Automatic language detection
- Text routing in multilingual systems
- Content filtering by language
2. **Machine Translation**
- Language-pair identification
- Translation system selection
3. **Content Analysis**
- Multilingual content categorization
- Language-specific content analysis
### Citation
If you use this dataset in your research, please cite:
```
@dataset{language_identification_2025,
author = {ProcessVenue Team},
website = {https://processvenue.com},
title = {Multilingual Headlines Language Identification Dataset},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/processvenue/language-identification},
version = {1.1}
}
```
###reference
```
1. @misc{disisbig_news_datasets,
author = {Gaurav},
title = {Indian Language News Datasets},
year = {2019},
publisher = {Kaggle},
url = {https://www.kaggle.com/datasets/disisbig/}
}
```
```
2. @misc{bhattarai_nepali_financial_news,
author = {Anuj Bhattarai},
title = {The Nepali Financial News Dataset},
year = {2024},
publisher = {Kaggle},
url = {https://www.kaggle.com/datasets/anujbhatrai/the-nepali-financial-news-dataset}
}
```
```
3. @misc{sourav_inshorts_hindi,
author = {Shivam Sourav},
title = {Inshorts-Hindi},
year = {2023},
publisher = {Kaggle},
url = {https://www.kaggle.com/datasets/shivamsourav2002/inshorts-hindi}
}
``` |