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

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']