Datasets:
File size: 1,485 Bytes
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---
license: cc-by-nc-sa-4.0
task_categories: ["automatic-speech-recognition"]
language: ["vi"]
pretty_name: VLSP 2020 - VinAI - ASR challenge dataset
size_categories: ["10K<n<100K"]
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 17159347574.893
num_examples: 56427
download_size: 11649243045
dataset_size: 17159347574.893
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# unofficial mirror of VLSP 2020 - VinAI - ASR challenge dataset
official announcement:
- tiếng việt: https://institute.vinbigdata.org/events/vinbigdata-chia-se-100-gio-du-lieu-tieng-noi-cho-cong-dong/
- in eglish: https://institute.vinbigdata.org/en/events/vinbigdata-shares-100-hour-data-for-the-community/
official download: https://drive.google.com/file/d/1vUSxdORDxk-ePUt-bUVDahpoXiqKchMx/view?usp=sharing
contact: info@vinbigdata.org
100h, 56.4k samples, accuracy 96%
pre-process: merge all transcript text files into 1, remove token `<unk>`
need to do: restore foreign words phonetised to vietnamese
usage with HuggingFace:
```python
# pip install -q "datasets[audio]"
from datasets import load_dataset
from torch.utils.data import DataLoader
dataset = load_dataset("doof-ferb/vlsp2020_vinai_100h", split="train", streaming=True)
dataset.set_format(type="torch", columns=["audio", "transcription"])
dataloader = DataLoader(dataset, batch_size=4)
``` |