librivox-indonesia / README.md
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metadata
pretty_name: LibriVox Indonesia 1.0
annotations_creators:
  - crowdsourced
language_creators:
  - crowdsourced
language:
  - ace
  - bal
  - bug
  - id
  - min
  - jav
  - sun
license: cc
multilinguality:
  - multilingual
size_categories:
  ace:
    - 1K<n<10K
  bal:
    - 1K<n<10K
  bug:
    - 1K<n<10K
  id:
    - 1K<n<10K
  min:
    - 1K<n<10K
  jav:
    - 1K<n<10K
  sun:
    - 1K<n<10K
source_datasets:
  - librivox
task_categories:
  - speech-processing
task_ids:
  - automatic-speech-recognition

Dataset Card for LibriVox Indonesia 1.0

Table of Contents

Dataset Description

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