pretty_name: LibriVox Indonesia 1.0
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ace
- ban
- bug
- ind
- min
- jav
- sun
license: cc
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
source_datasets:
- librivox
task_categories:
- automatic-speech-recognition
Dataset Card for LibriVox Indonesia 1.0
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia
- Repository: https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia
- Point of Contact: Cahya Wirawan
Dataset Summary
The LibriVox Indonesia dataset consists of MP3 audio and a corresponding text file we generated from the public domain audiobooks LibriVox. We collected only languages in Indonesia for this dataset. The original LibriVox audiobooks or sound files' duration varies from a few minutes to a few hours. Each audio file in the speech dataset now lasts from a few seconds to a maximum of 20 seconds.
We converted the audiobooks to speech datasets using the forced alignment software we developed. It supports multilingual, including low-resource languages, such as Acehnese, Balinese, or Minangkabau. We can also use it for other languages without additional work to train the model.
The dataset currently consists of 8 hours in 7 languages from Indonesia. We will add more languages or audio files as we collect them.
Languages
Acehnese, Balinese, Bugisnese, Indonesian, Minangkabau, Javanese, Sundanese
Dataset Structure
Data Instances
A typical data point comprises the path to the audio file and its sentence. Additional fields include
reader and language.
{
'path': 'librivox-indonesia/sundanese/universal-declaration-of-human-rights/human_rights_un_sun_brc_0000.mp3',
'language': 'sun',
'reader': '3174',
'sentence': 'pernyataan umum ngeunaan hak hak asasi manusa sakabeh manusa',
'audio': {
'path': 'librivox-indonesia/sundanese/universal-declaration-of-human-rights/human_rights_un_sun_brc_0000.mp3',
'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32),
'sampling_rate': 44100
},
}
Data Fields
path (string): The path to the audio file
language (string): The language of the audio file
reader (string): The reader Id in LibriVox
sentence (string): The sentence the user read from the book.
audio (dict): 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 to dataset.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 over dataset["audio"][0].
Data Splits
The speech material has only train split.
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
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
Public Domain, CC-0
Citation Information