The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for VIVOS
Dataset Summary
VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for Vietnamese Automatic Speech Recognition task.
The corpus was prepared by AILAB, a computer science lab of VNUHCM - University of Science, with Prof. Vu Hai Quan is the head of.
We publish this corpus in hope to attract more scientists to solve Vietnamese speech recognition problems.
Supported Tasks and Leaderboards
[Needs More Information]
Languages
Vietnamese
Dataset Structure
Data Instances
A typical data point comprises the path to the audio file, called path
and its transcription, called sentence
. Some additional information about the speaker and the passage which contains the transcription is provided.
{'speaker_id': 'VIVOSSPK01',
'path': '/home/admin/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/vivos/train/waves/VIVOSSPK01/VIVOSSPK01_R001.wav',
'audio': {'path': '/home/admin/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/vivos/train/waves/VIVOSSPK01/VIVOSSPK01_R001.wav',
'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32),
'sampling_rate': 16000},
'sentence': 'KHÁCH SẠN'}
Data Fields
speaker_id: An id for which speaker (voice) made the recording
path: The path to the audio file
audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column:
dataset[0]["audio"]
the audio file is automatically decoded and resampled todataset.features["audio"].sampling_rate
. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the"audio"
column, i.e.dataset[0]["audio"]
should always be preferred overdataset["audio"][0]
.sentence: The sentence the user was prompted to speak
Data Splits
The speech material has been subdivided into portions for train and test.
Speech was recorded in a quiet environment with high quality microphone, speakers were asked to read one sentence at a time.
Train | Test | |
---|---|---|
Speakers | 46 | 19 |
Utterances | 11660 | 760 |
Duration | 14:55 | 00:45 |
Unique Syllables | 4617 | 1692 |
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset.
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
Dataset provided for research purposes only. Please check dataset license for additional information.
Additional Information
Dataset Curators
The dataset was initially prepared by AILAB, a computer science lab of VNUHCM - University of Science.
Licensing Information
Public Domain, Creative Commons Attribution NonCommercial ShareAlike v4.0 (CC BY-NC-SA 4.0)
Citation Information
@inproceedings{luong-vu-2016-non,
title = "A non-expert {K}aldi recipe for {V}ietnamese Speech Recognition System",
author = "Luong, Hieu-Thi and
Vu, Hai-Quan",
booktitle = "Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies ({WLSI}/{OIAF}4{HLT}2016)",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-5207",
pages = "51--55",
}
Contributions
Thanks to @binh234 for adding this dataset.
- Downloads last month
- 38