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F_01_OISHI_S_10_ANGRY_1
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F_01_OISHI_S_10_ANGRY_3
F_01_OISHI_S_10_ANGRY_4
F_01_OISHI_S_10_ANGRY_5
F_01_OISHI_S_10_DISGUST_1
F_01_OISHI_S_10_DISGUST_2
F_01_OISHI_S_10_DISGUST_3
F_01_OISHI_S_10_DISGUST_4
F_01_OISHI_S_10_DISGUST_5
F_01_OISHI_S_10_FEAR_1
F_01_OISHI_S_10_FEAR_2
F_01_OISHI_S_10_FEAR_3
F_01_OISHI_S_10_FEAR_4
F_01_OISHI_S_10_FEAR_5
F_01_OISHI_S_10_HAPPY_1
F_01_OISHI_S_10_HAPPY_2
F_01_OISHI_S_10_HAPPY_3
F_01_OISHI_S_10_HAPPY_4
F_01_OISHI_S_10_HAPPY_5
F_01_OISHI_S_10_NEUTRAL_1
F_01_OISHI_S_10_NEUTRAL_2
F_01_OISHI_S_10_NEUTRAL_3
F_01_OISHI_S_10_NEUTRAL_4
F_01_OISHI_S_10_NEUTRAL_5
F_01_OISHI_S_10_SAD_1
F_01_OISHI_S_10_SAD_2
F_01_OISHI_S_10_SAD_3
F_01_OISHI_S_10_SAD_4
F_01_OISHI_S_10_SAD_5
F_01_OISHI_S_10_SURPRISE_1
F_01_OISHI_S_10_SURPRISE_2
F_01_OISHI_S_10_SURPRISE_3
F_01_OISHI_S_10_SURPRISE_4
F_01_OISHI_S_10_SURPRISE_5
F_01_OISHI_S_1_ANGRY_1
F_01_OISHI_S_1_ANGRY_2
F_01_OISHI_S_1_ANGRY_3
F_01_OISHI_S_1_ANGRY_4
F_01_OISHI_S_1_ANGRY_5
F_01_OISHI_S_1_DISGUST_1
F_01_OISHI_S_1_DISGUST_2
F_01_OISHI_S_1_DISGUST_3
F_01_OISHI_S_1_DISGUST_4
F_01_OISHI_S_1_DISGUST_5
F_01_OISHI_S_1_FEAR_1
F_01_OISHI_S_1_FEAR_2
F_01_OISHI_S_1_FEAR_3
F_01_OISHI_S_1_FEAR_4
F_01_OISHI_S_1_FEAR_5
F_01_OISHI_S_1_HAPPY_1
F_01_OISHI_S_1_HAPPY_2
F_01_OISHI_S_1_HAPPY_3
F_01_OISHI_S_1_HAPPY_4
F_01_OISHI_S_1_HAPPY_5
F_01_OISHI_S_1_NEUTRAL_1
F_01_OISHI_S_1_NEUTRAL_2
F_01_OISHI_S_1_NEUTRAL_3
F_01_OISHI_S_1_NEUTRAL_4
F_01_OISHI_S_1_NEUTRAL_5
F_01_OISHI_S_1_SAD_1
F_01_OISHI_S_1_SAD_2
F_01_OISHI_S_1_SAD_3
F_01_OISHI_S_1_SAD_4
F_01_OISHI_S_1_SAD_5
F_01_OISHI_S_1_SURPRISE_1
F_01_OISHI_S_1_SURPRISE_2
F_01_OISHI_S_1_SURPRISE_3
F_01_OISHI_S_1_SURPRISE_4
F_01_OISHI_S_1_SURPRISE_5
F_01_OISHI_S_2_ANGRY_1
F_01_OISHI_S_2_ANGRY_2
F_01_OISHI_S_2_ANGRY_3
F_01_OISHI_S_2_ANGRY_4
F_01_OISHI_S_2_ANGRY_5
F_01_OISHI_S_2_DISGUST_1
F_01_OISHI_S_2_DISGUST_2
F_01_OISHI_S_2_DISGUST_3
F_01_OISHI_S_2_DISGUST_4
F_01_OISHI_S_2_DISGUST_5
F_01_OISHI_S_2_FEAR_1
F_01_OISHI_S_2_FEAR_2
F_01_OISHI_S_2_FEAR_3
F_01_OISHI_S_2_FEAR_4
F_01_OISHI_S_2_FEAR_5
F_01_OISHI_S_2_HAPPY_1
F_01_OISHI_S_2_HAPPY_2
F_01_OISHI_S_2_HAPPY_3
F_01_OISHI_S_2_HAPPY_4
F_01_OISHI_S_2_HAPPY_5
F_01_OISHI_S_2_NEUTRAL_1
F_01_OISHI_S_2_NEUTRAL_2
F_01_OISHI_S_2_NEUTRAL_3
F_01_OISHI_S_2_NEUTRAL_4
F_01_OISHI_S_2_NEUTRAL_5
F_01_OISHI_S_2_SAD_1
F_01_OISHI_S_2_SAD_2
F_01_OISHI_S_2_SAD_3
F_01_OISHI_S_2_SAD_4
F_01_OISHI_S_2_SAD_5

SUST BANGLA EMOTIONAL SPEECH CORPUS

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("sustcsenlp/bn_emotion_speech_corpus",split="train")

Naming Convention

Each audio file in the dataset has a unique name. There are eight parts in the file name where all the parts are connected by underscores. The order of all the parts is organized as: Gender-Speaker's serial number-Speaker's name-Unit of recording-Unit number- Emotion name- Repeating number and the File format.

For example, the filename F_02_MONIKA_S_1_NEUTRAL_5.wav refers to:

Symbol Meaning
F Speaker Gender
02 Speaker Number
MONIKA Speaker Name
S_1 Sentence Number
NEUTRAL Emotion
5 Take Number

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

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

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