---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
- text-to-speech
language:
- vi
pretty_name: a novel large-scale Vietnamese speech corpus (LSVSC)
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  - name: topic
    dtype: string
  - name: gender
    dtype: string
  - name: dialect
    dtype: string
  - name: emotion
    dtype: string
  - name: age
    dtype: string
  splits:
  - name: train
    num_bytes: 8620435812.644
    num_examples: 45458
  - name: validation
    num_bytes: 1102706521.852
    num_examples: 5682
  - name: test
    num_bytes: 1136311929.744
    num_examples: 5683
  download_size: 11575801683
  dataset_size: 10859454264.239998
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

# unofficial mirror of LSVSC dataset (novel large-scale Vietnamese speech corpus)

official announcement: https://www.mdpi.com/2079-9292/13/5/977

official download: https://drive.google.com/drive/folders/1tiPKaIOC7bt6isv5qFqf61O_2jFK8ZOI

100h, 57k samples

pre-process: remove non-sense characters: `\r` `\n`

need to do: check misspelling, 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/LSVSC", split="train", streaming=True)
dataset.set_format(type="torch", columns=["audio", "transcription"])
dataloader = DataLoader(dataset, batch_size=4)
```