task_categories:audio-classification language:en license:cc-by-nc-nd-4.0 code legal region:us
The audio dataset consists of a collection of texts spoken with four distinct
emotions. These texts are spoken in English and represent four different
emotional states: **euphoria, joy, sadness and surprise**.
Each audio clip captures the tone, intonation, and nuances of speech as
individuals convey their emotions through their voice.
The dataset includes a diverse range of speakers, ensuring variability in age,
gender, and cultural backgrounds*, allowing for a more comprehensive
representation of the emotional spectrum.
The dataset is labeled and organized based on the emotion expressed in each
audio sample, making it a valuable resource for emotion recognition and
analysis. Researchers and developers can utilize this dataset to train and
evaluate machine learning models and algorithms, aiming to accurately
recognize and classify emotions in speech.
@InProceedings{huggingface:dataset,
title = {speech-emotion-recognition-dataset},
author = {TrainingDataPro},
year = {2023}
}
---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- audio-classification
tags:
- code
- legal
dataset_info:
  features:
  - name: set_id
    dtype: string
  - name: euphoric
    dtype: audio
  - name: joyfully
    dtype: audio
  - name: sad
    dtype: audio
  - name: surprised
    dtype: audio
  - name: text
    dtype: string
  - name: gender
    dtype: string
  - name: age
    dtype: int8
  - name: country
    dtype: string
  splits:
  - name: train
    num_bytes: 17202
    num_examples: 20
  download_size: 28409585
  dataset_size: 17202
---

# Emotions on Audio Dataset

The audio dataset consists of a collection of texts spoken with four distinct emotions. These texts are spoken in English and represent four different emotional states: **euphoria, joy, sadness and surprise**. 
Each audio clip captures the tone, intonation, and nuances of speech as individuals convey their emotions through their voice. 

The dataset includes a diverse range of speakers, ensuring variability in *age, gender, and cultural backgrounds*, allowing for a more comprehensive representation of the emotional spectrum.

The dataset is labeled and organized based on the emotion expressed in each audio sample, making it a valuable resource for emotion recognition and analysis. Researchers and developers can utilize this dataset to train and evaluate machine learning models and algorithms, aiming to accurately recognize and classify emotions in speech.

### The audio dataset also provides an opportunity for various applications:
- sentiment analysis
- automatic emotion detection
- emotional speech synthesis. 
- voice assistants
- customer service
- mental health analysis
- entertainment industries

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F618942%2F94459eaec038a29404e3a7afef3fb88c%2Faudio0.png?generation=1689235055331390&alt=media)

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=speech-emotion-recognition-dataset) to discuss your requirements, learn about the price and buy the dataset.

# Content

- **files**: includes folders corresponding to people and containing text spoken in English in 4 different manners: **euphoric, joyfully, sad and surprised**
- **.csv** file: contains information about people in the dataset

### File with the extension .csv

includes the following information for each set of media files:

- **set_id**: link to the set of audio files,
- **text**: text spoken in the audio set, 
- **gender**: gender of the person, 
- **age**: age of the person,
- **country**: country of the person

# Audio with emotions might be collected in accordance with your requirements.

## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=speech-emotion-recognition-dataset) provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**