README.md

Dataset Card for Language Identification Dataset

Dataset Description

• Repository: processvenue/language_identification
• Total Samples: 135784
• Number of Languages: 18
• Splits:
  • Train: 104849 samples (70%)
  • Validation: 15467 samples (15%)
  • Test: 15468 samples (15%)

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

Language Details

1. Hindi (hi): Major language of India, written in Devanagari script
2. Urdu (ur): Written in Perso-Arabic script
3. Bengali (bn): Official language of Bangladesh and several Indian states
4. Gujarati (gu): Official language of Gujarat
5. Kannada (kn): Official language of Karnataka
6. Malayalam (ml): Official language of Kerala
7. Marathi (mr): Official language of Maharashtra
8. Odia (or): Official language of Odisha
9. Punjabi (pa): Official language of Punjab
10. Tamil (ta): Official language of Tamil Nadu and Singapore
11. Telugu (te): Official language of Telangana and Andhra Pradesh
12. Sanskrit (sa): Ancient language of India, written in Devanagari script
13. Konkani (kok): Official language of Goa
14. Sindhi (sd): Official language of Sindh province in Pakistan
15. Nepali (ne): Official language of Nepal
16. Assamese (as): Official language of Assam
17. Kashmiri (ks): Official language of Jammu and Kashmir
18. English (en): Official language of India

Data Fields

• Headline: The input text sample
• Language: The language label (one of the 18 languages listed above)

Usage Example

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("processvenue/language_identification")

# 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}
    }