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README.md
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license: mit
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---
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---
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license: mit
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task_categories:
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- audio-classification
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language:
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- bn
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pretty_name: SUST BANGLA EMOTIONAL SPEECH CORPUS
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size_categories:
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- 1K<n<10K
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# SUST BANGLA EMOTIONAL SPEECH CORPUS
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## Dataset Description
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- **Homepage:**
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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- **Point of Contact:** [Sadia Sultana]([email protected])
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### Dataset Summary
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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.
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https://doi.org/10.1371/journal.pone.0250173
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### Downloading the data
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'''
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from datasets import load_dataset
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test = load_dataset("sustcsenlp/bn_emotion_speech_corpus",split="train")
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'''
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### Naming Convention
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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.
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For example, the filename F_02_MONIKA_S_1_NEUTRAL_5.wav refers to:
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| Symbol | Meaning |
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| ----------- | ----------- |
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| F | Speaker Gender |
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| 02 | Speaker Number |
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| MONIKA | Speaker Name |
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| S_1 | Sentence Number |
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| NEUTRAL | Emotion |
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| 5 | Take Number |
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### Languages
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This dataset contains Bangla Audio Data.
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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### Contributions
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[More Information Needed]
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