Datasets:
File size: 1,665 Bytes
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---
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)
``` |