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: test
      num_bytes: 2345138893.961
      num_examples: 6533
    - name: validation
      num_bytes: 2374606148.554
      num_examples: 6594
    - name: train
      num_bytes: 23111288170.312
      num_examples: 64491
  download_size: 31898660522
  dataset_size: 27831033212.827
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
      - split: validation
        path: data/validation-*
      - split: train
        path: data/train-*
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

• Developed By Shahjalal University of Science and Technology, Bangladesh
• Repository: [Needs More Information]
• Paper: Bangladeshi Bangla speech corpus for automatic speech recognition research
• Leaderboard: [Needs More Information]
• Point of Contact: A. M. Samin

Dataset Summary

SUBAK.KO, a publicly available annotated Bangladeshi standard Bangla speech corpus is compiled for automatic speech recognition research. This corpus contains 241 hours of high-quality speech data, including 229 hours of read speech data and 12 hours of broadcast speech data. The read speech segment is recorded in a noise-proof studio environment from 33 male and 28 female native Bangladeshi Bangla speakers representing 8 divisions/34 districts of Bangladesh. Furthermore, the read speech segment comprises a total of 1 hour and 30 minutes of recorded speech provided by two second language (L2) speakers. The broadcast speech segment is collected from YouTube. SUBAK.KO has been manually annotated under human supervision. The associated paper reports detailed information about the development and baseline performance of SUBAK.KO.

SUBAK.KO is developed by the Department of Computer Science and Engineering (CSE) at Shahjalal University of Science and Technology (SUST), Bangladesh with financial support from the Higher Education Quality Enhancement Project (AIF Window 4, CP 3888) for “The Development of Multi-Platform Speech and Language Processing Software for Bangla” of the University Grants Commission (UGC), Bangladesh.

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

Additional Information

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}
}