README.md

---
dataset_info:
  features:
  - name: correct
    dtype: string
  - name: incorrect
    dtype: string
  splits:
  - name: train
    num_bytes: 1211373359.8361242
    num_examples: 3161164
  - name: test
    num_bytes: 151421861.5819379
    num_examples: 395146
  - name: validation
    num_bytes: 151421861.5819379
    num_examples: 395146
  download_size: 752362217
  dataset_size: 1514217083
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: validation
    path: data/validation-*
language:
- dv
license: apache-2.0
pretty_name: dv_text_erros
---

# DV Text Errors

Dhivehi text error correction dataset containing correct sentences and synthetically generated errors. The dataset aims to test Dhivehi language error correction models and tools.

## About Dataset

- **Task**: Text error correction
- **Language**: Dhivehi (dv)

## Dataset Structure

Input-output pairs of Dhivehi text:
- `correct`: Original correct sentences
- `incorrect`: Sentences with synthetic errors

## Statistics

- Train set: {train_examples} examples ({0.7999997975429817}%)
- Test set: {test_examples} examples ({0.10000010122850919}%)
- Validation set: {val_examples} examples ({0.10000010122850919}%)

**Details:**
- Unique words: {448628}

```json
{
  "total_examples": {
    "train": 3161164,
    "test": 395146,
    "validation": 395146
  },
  "avg_sentence_length": {
    "train": 11.968980097204701,
    "test": 11.961302910822836,
    "validation": 11.973824864733542
  },
  "error_distribution": {
    "min": 0,
    "max": 2411,
    "avg": 64.85144965588626
  }
}
```

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("alakxender/dv-synthetic-errors")
```

## Dataset Creation

Created using:
- Source: Collection of Dhivehi articles
- Error generation: Character and diacritic substitutions
- Error rate: 30% per word probability