README.md

---
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](#dataset-card-for-SUBAK.KO)
  - [Table of Contents](#table-of-contents)
  - [Dataset Description](#dataset-description)
    - [Dataset Summary](#dataset-summary)
    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
    - [Languages](#languages)
  - [Dataset Structure](#dataset-structure)
    - [Data Instances](#data-instances)
    - [Data Fields](#data-fields)
    - [Data Splits](#data-splits)
  - [Dataset Creation](#dataset-creation)
    - [Curation Rationale](#curation-rationale)
    - [Source Data](#source-data)
      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
      - [Who are the source language producers?](#who-are-the-source-language-producers)
    - [Annotations](#annotations)
      - [Annotation process](#annotation-process)
      - [Who are the annotators?](#who-are-the-annotators)
    - [Personal and Sensitive Information](#personal-and-sensitive-information)
  - [Considerations for Using the Data](#considerations-for-using-the-data)
    - [Social Impact of Dataset](#social-impact-of-dataset)
    - [Discussion of Biases](#discussion-of-biases)
    - [Other Known Limitations](#other-known-limitations)
  - [Additional Information](#additional-information)
    - [Dataset Curators](#dataset-curators)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)
    - [Contributions](#contributions)

## Dataset Description

- **Developed By** Dept. of CSE, SUST, Bangladesh
- **Paper:** [Bangladeshi Bangla speech corpus for automatic speech recognition research](https://www.sciencedirect.com/science/article/abs/pii/S0167639321001370)
- **Point of Contact:** [Prof. Dr. M. Shahidur Rahman](mailto:[email protected])

### 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 [corresponding paper](https://www.sciencedirect.com/science/article/abs/pii/S0167639321001370) reports detailed information about 
the development and baseline performance of SUBAK.KO. 

SUBAK.KO is developed by the researchers from 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.


### Example Usage
To download the full SUBAK.KO corpus, use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("ahnafsamin/SUBAK.KO")
```

Alternatively, you can manually download the zipped SUBAK.KO folder from [this HuggingFace directory.](https://huggingface.co/datasets/ahnafsamin/SUBAK.KO/tree/main/Data)
The csv files corresponding to the train, validation and test splits can be found in the same directory. 

### 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 and its transcription.

```
{
 'audio': {'path': '/home/username/subakko/part5/wav5/e4/TNM22_MESBA_page_257-258_5_5_Labeled_by_Tomal-20.wav',
		   'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32),
		   'sampling_rate': 16000},
 'transcript': 'তারপর চার মাস তিনি ছিলেন কেন্দ্রীয় গোয়েন্দা সংস্থার তত্বাবধানে এক নিরাপদ জায়গায়',
 'path': '/subakko/part5/wav5/e4/TNM22_MESBA_page_257-258_5_5_Labeled_by_Tomal-20.wav'
}
```

### Data Fields

- audio: A dictionary containing the path to the original 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]`.

- transcription: The orthographic transcription

- file_path: The relative path to the audio file

### Data Splits

SUBAK.KO has been subdivided into three splits for train, validation and test. It is strongly advised to use identical data splits 
for research purposes to facilitate benchmarking across various models.


|                  | Train    | Validation | Test     |
| ---------------- | ---------|------------|----------|      
| Utterances       | 64491    | 6594       | 6533     |
| Duration         | 200.3 hrs| 20.3 hrs   | 20.3 hrs |


## Additional Information

### Licensing Information

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/deed.en)

### Citation Information
Please cite the following paper if you use the corpus.

```
@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}
}
```