README.md

metadata

language:
  - bn
license: cc-by-4.0
size_categories:
  - 10K<n<100K
task_categories:
  - automatic-speech-recognition
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: 2345138893.961
      num_examples: 6533
    - name: validation
      num_bytes: 2374606148.554
      num_examples: 6594
  download_size: 9276258873
  dataset_size: 4737418001.515
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
      - split: validation
        path: data/validation-*
tags:
  - speech-recognition
  - Bangladeshi Bangla
  - Bengali
  - speech-corpus

Dataset Card for SUBAK.KO

Table of Contents

• Dataset Card for SUBAK.KO
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
    • Annotations
      • Annotation process
      • Who are the annotators?
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information
    • Contributions

Dataset Description

• Homepage: https://doi.org/10.5281/zenodo.7068130
• Repository: [Needs More Information]
• Paper: Bangladeshi Bangla speech corpus for automatic speech recognition research
• Leaderboard: [Needs More Information]
• Point of Contact: AILAB

Dataset Summary

SUBAK.KO is a Bangladeshi standard Bangla annotated speech corpus for automatic speech recognition research. The corpus contains 241 hours of high quality speech data, including 229 hours of read speech data collected in an studio environment and 12 hours of broadcast speech data.

Supported Tasks and Leaderboards

This dataset is designed for the automatic speech recognition task. The associated paper provides the baseline results on SUBAK.KO corpus.

Languages

Bangladeshi standard Bangla

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

@article{kibria2022bangladeshi,
  title={Bangladeshi Bangla speech corpus for automatic speech recognition research},
  author={Kibria, Shafkat and Samin, Ahnaf Mozib and Kobir, M Humayon and Rahman, M Shahidur and Selim, M Reza and Iqbal, M Zafar},
  journal={Speech Communication},
  volume={136},
  pages={84--97},
  year={2022},
  publisher={Elsevier}
}