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Datasets:
SUST-CSE-Speech
/
SUBAK.KO

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Text
Formats:
parquet
Languages:
Bengali
Size:
10K - 100K
Tags:
speech-recognition
Bangladeshi Bangla
Bengali
speech-corpus
Libraries:
Datasets
Dask
License:
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SUBAK.KO / README.md
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metadata
license: cc-by-4.0
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: transcription
      dtype: string
    - name: file_path
      dtype: string
  splits:
    - name: train
      num_bytes: 17672959
      num_examples: 50
    - name: test
      num_bytes: 2561925946.804
      num_examples: 6533
    - name: validation
      num_bytes: 2611590022.354
      num_examples: 6594
  download_size: 4644261004
  dataset_size: 5191188928.158
  configs:
    - config_name: default
  data_files:
    - split: test
      path: data/test-*
    - split: validation
      path: data/validation-*

pretty_name: VIVOS annotations_creators: - expert-generated language_creators: - crowdsourced - expert-generated language: - vi license: - cc-by-nc-sa-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - automatic-speech-recognition task_ids: [] dataset_info: features: - name: speaker_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string splits: - name: train num_bytes: 1722002133 num_examples: 11660 - name: test num_bytes: 86120227 num_examples: 760 download_size: 1475540500 dataset_size: 1808122360

Dataset Card for VIVOS

Table of Contents

Dataset Description

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 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].

  • 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.