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---
license: mit
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:** 
- **Repository:** 
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** [Sadia Sultana](sadia-cse@sust.edu)

### 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 Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### 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]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]