metadata

license: cc-by-4.0
task_categories:
  - audio-classification
language:
  - bn
pretty_name: SUST BANGLA EMOTIONAL SPEECH CORPUS
size_categories:
  - 1K<n<10K

SUST BANGLA EMOTIONAL SPEECH CORPUS

Dataset Description

Homepage: bn_emotion_speech_corpus
Repository:
Paper: SUBESCO PAPER
Leaderboard:
Point of Contact: Sadia Sultana

Dataset Summary

SUBESCO is an audio-only emotional speech corpus of 7000 sentence-level utterances of the Bangla language. 20 professional actors (10 males and 10 females) participated in the recordings of 10 sentences for 7 target emotions. The emotions are Anger, Disgust, Fear, Happiness, Neutral, Sadness and Surprise. Total duration of the corpus is 7 hours 40 min 40 sec. Total size of the dataset is 2.03 GB. The dataset was evaluated by 50 raters (25 males, 25 females). Human perception test achieved a raw accuracy of 71%. All the details relating to creation, evaluation and analysis of SUBESCO have been described in the corresponding journal paper which has been published in Plos One.

https://doi.org/10.1371/journal.pone.0250173

Downloading the data

from datasets import load_dataset

train = load_dataset("sajid73/SUBESCO-audio-dataset", split="train")

Languages

This dataset contains Bangla Audio Data.

Dataset Creation

This database was created as a part of PhD thesis project of the author Sadia Sultana. It was designed and developed by the author in the Department of Computer Science and Engineering of Shahjalal University of Science and Technology. Financial grant was supported by the university. If you use the dataset please cite SUBESCO and the corresponding academic journal publication in Plos One.

Citation Information

@dataset{sadia_sultana_2021_4526477,
  author       = {Sadia Sultana},
  title        = {SUST Bangla Emotional Speech Corpus (SUBESCO)},
  month        = feb,
  year         = 2021,
  note         = {{This database was created as a part of PhD thesis 
                   project of the author Sadia Sultana. It was
                   designed and developed by the author in the
                   Department of Computer Science and Engineering  of
                   Shahjalal University of Science and Technology.
                   Financial grant was supported by the university.
                   If you use the dataset please cite SUBESCO and the
                   corresponding academic journal publication in Plos
                   One.}},
  publisher    = {Zenodo},
  version      = {version - 1.1},
  doi          = {10.5281/zenodo.4526477},
  url          = {https://doi.org/10.5281/zenodo.4526477}
}

Contributors

Name	University
Sadia Sultana	Shahjalal University of Science and Technology
Dr. M. Zafar Iqbal	Shahjalal University of Science and Technology
Dr. M. Shahidur Rahman	Shahjalal University of Science and Technology