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# 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



```python

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}

    }

```