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