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---
dataset_info:
features:
- name: sex
dtype: string
- name: duration
dtype: float64
- name: transcript
dtype: string
- name: audio
dtype: audio
- name: id
dtype: int64
splits:
- name: train
num_bytes: 13262971934.88
num_examples: 65120
- name: validation
num_bytes: 1164972031.672
num_examples: 5663
- name: test
num_bytes: 2537956206.612
num_examples: 12492
download_size: 14740834520
dataset_size: 16965900173.163998
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
[](https://huggingface.co/datasets/ming030890/mdcc)
# MDCC: A New Cantonese ASR Dataset
## 📦 Update [1 Feb, 2024]
The `.wav` data of the dataset is available here:
🔗 [Google Drive Link](https://drive.google.com/file/d/1epfYMMhXdBKA6nxPgUugb2Uj4DllSxkn/view?usp=drive_link)
**Note:** For research purposes only.
---
## 📖 Overview
MDCC (“**M**ulti-**D**omain **C**antonese **C**orpus”) is a large-scale Cantonese automatic speech recognition (ASR) dataset compiled from multiple domains. It provides:
- **Audio**: `.wav` recordings of spontaneous and read speech
- **Transcript**: UTF‑8 plain‑text transcripts
- **Speaker metadata**: sex
- **Duration**: audio length in seconds
This repo contains metadata files and a conversion script to turn the data into a Hugging Face-compatible dataset.
---
## 📝 Paper & Citation
Tiezheng Yu, Rita Frieske, Peng Xu, Samuel Cahyawijaya, Cheuk Tung Shadow Yiu, Holy Lovenia,
Wenliang Dai, Elham J. Barezi, Qifeng Chen, Xiaojuan Ma, Bertram E. Shi & Pascale Fung
**“Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset”**
📄 [arXiv:2201.02419](https://arxiv.org/pdf/2201.02419.pdf)
```bibtex
@misc{yu2022automatic,
title = {Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset},
author = {Tiezheng Yu and Rita Frieske and Peng Xu and Samuel Cahyawijaya and
Cheuk Tung Shadow Yiu and Holy Lovenia and Wenliang Dai and
Elham J. Barezi and Qifeng Chen and Xiaojuan Ma and
Bertram E. Shi and Pascale Fung},
year = {2022},
eprint = {2201.02419},
archivePrefix= {arXiv},
primaryClass = {cs.CL}
}
```
---
## 🚀 How to Load on Hugging Face
```python
from datasets import load_dataset
ds = load_dataset("ming030890/mdcc")
print(ds["train"][0])
```
Example output:
```python
{
'audio': {
'path': '/path/to/audio.wav',
'array': [...],
'sampling_rate': 16000
},
'transcript': '你好，歡迎收聽…',
'sex': 'female',
'duration': 3.08
}
```
---
## 🔓 License & Access
1. Review the `MDCC_LICENSE` file in this repo.
2. Sign it and send to **chinatysonyu@gmail.com**.
3. Then download the dataset here:
🔗 [Google Drive Folder](https://drive.google.com/drive/folders/1HhNqrPpUTtjsJ0wZQCSKqet7ftmWb6eI?usp=sharing)
---
## ✅ Checkpoints
Download pretrained models here:
🔗 [Checkpoints Google Drive](https://drive.google.com/drive/folders/1BpGGOfr4IDYv0cWTowsDKkVmud7tNYzy?usp=sharing)
---
## ⚠️ Disclaimer
I am **not the original author** of the dataset or the research paper.
This repo only provides a Hugging Face-compatible version of the public MDCC data.
For the original codebase and documentation, refer to:
🔗 https://github.com/HLTCHKUST/cantonese-asr
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