Update README.md

README.md

@@ -1,3 +1,69 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+task_categories:
+- translation
+language:
+- vi
+size_categories:
+- 10K<n<100K
+pretty_name: ViDia2Std
+tags:
+- dialect-normalization
+- vietnamese-dialect
+- social-media
+- low-resource
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train.csv
+  - split: validation
+    path: dev.csv
+  - split: test
+    path: test.csv
+---
+
+# ViDia2Std: A Parallel Corpus for Vietnamese Dialect-to-Standard Translation
+
+**ViDia2Std** is a high-quality, manually annotated parallel corpus for translating Vietnamese dialects (Northern, Central, Southern) into Standard Vietnamese. Sourced from authentic social media comments across all 63 provinces of Vietnam, it serves as a benchmark for dialect normalization and adaptation tasks.
+
+This dataset accompanies the paper: **"ViDia2Std: A Parallel Corpus and Methods for Low-Resource Vietnamese Dialect-to-Standard Translation"** (Accepted at AAAI-26).
+
+## 📂 Dataset Structure
+
+The dataset is split into three files:
+
+* **`train.csv`**: The training set (10,870 pairs).
+* **`dev.csv`**: The development/validation set (1,184 pairs).
+* **`test.csv`**: The testing set (1,603 pairs).
+
+### 📝 Data Fields
+
+| Column | Description |
+| :--- | :--- |
+| **`dialect`** | The original dialectal input sentence (source). Contains regional words, and non-standard grammar. |
+| **`standard`** | The manually normalized Standard Vietnamese sentence (target). Equivalent in meaning and intent to the source. |
+| **`region`** | The dialect region of the source sentence: `northern`, `central`, or `southern`. |
+| **`sentiment`** | *(Only in `test.csv`)* The sentiment label of the sentence (`positive`, `negative`, `neutral`). Used for extrinsic evaluation. |
+
+## 📊 Statistics
+
+| Split | Samples |
+| :--- | :--- |
+| **Train** | 10,870 |
+| **Dev** | 1,184 |
+| **Test** | 1,603 |
+| **Total** | **13,657** |
+
+## 🚀 Usage
+
+### Loading with Pandas
+```python
+import pandas as pd
+
+train_df = pd.read_csv("train.csv")
+print(train_df.head())
+
+# Accessing specific columns
+inputs = train_df['dialect']
+targets = train_df['standard']