README.md

metadata

language:
  - vi
license: other
task_categories:
  - audio-classification
  - automatic-speech-recognition
pretty_name: ViMD Truncated 10s (16kHz)
size_categories:
  - 10K<n<100K

ViMD Truncated 10s — 16kHz

Preprocessed version of ViMD (Nguyen et al., EMNLP 2024) for Dialect Identification.

Preprocessing applied

• Resample: 44.1kHz (original) → 16kHz, mono
• Truncate: only the FIRST 10 SECONDS of each audio are kept (files shorter than 10s are kept intact). 1 original file = 1 sample. This follows the truncation strategy of Lu et al. (2020), NOT chunking.
• Splits: original ViMD train/valid/test kept unchanged (speaker-exclusive).

New column vs. original ViMD

• new_province: province name after the administrative merger (34 classes), mapped from the original province column (63 classes).

Usage

from datasets import load_dataset
ds = load_dataset("tannhoo06/ViMD_preprocessing")

EDA without downloading audio

import pandas as pd
meta = pd.read_parquet("hf://datasets/tannhoo06/ViMD_preprocessing/metadata.parquet")

Citation

Please cite the original ViMD paper (Nguyen et al., EMNLP 2024).