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RAVDESS Dataset

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Visualization of the RAVDESS dataset in the Deep Lake UI

RAVDESS dataset

What is RAVDESS Dataset?

The Ryerson Audio-Visual Database of Emotional Speech and Song Dataset (Ravdees) consists of 7356 files database (total size: 24.8 GB). Two lexically-matched phrases are vocalized in a neutral North American dialect by 24 professional actors (12 female, 12 male). There are calm, happy, sad, angry, terrified, surprised, and disgusted expressions in speech, and there are calm, happy, sad, angry, and frightening expressions in music.

Download RAVDESS Dataset in Python

Instead of downloading the RAVDESS dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load RAVDESS Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/ravdess-emotional-speech-audio")

RAVDESS Dataset Structure

RAVDESS Data Fields
  • audios: tensor representing the audio files in wave format.
  • modalities: a tensor to represent various modalities of the audio.
  • vocal_channels: tensor to represent various vocal channels in audio.
  • emotions: tensor representing various emotions related to the audio file.
  • emotional_intensities: class label tensor representing various emotional intensities.
  • statements: tensor representing the text read in audio.
  • repetitions: tensor representing 1st or 2nd repetition.
  • genders: tensor to distinguish male or female audio.
RAVDESS Data Splits

How to use RAVDESS Dataset with PyTorch and TensorFlow in Python

Train a model on the RAVDESS dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
Train a model on the RAVDESS dataset with TensorFlow in Python
				
					dataloader = ds.tensorflow()

Additional Information about RAVDESS Dataset

RAVDESS Dataset Description

RAVDESS Dataset Curators

Livingstone SR, Russo FA

RAVDESS Dataset Licensing Information

Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.

If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

RAVDESS Dataset Citation Information
				
					@inproceedings{,
  title = {The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS)},
  author = {Livingstone SR, Russo FA},
  booktitle = {A dynamic, multimodal set of facial and vocal expressions in North American English. PLoS ONE 13(5): e0196391},
  year = {2018} 
}

RAVDESS Dataset FAQs

What is the RAVDESS dataset for Python?

The Ryerson Audio-Visual Database of Emotional Speech and Song Dataset (Ravdees) comprises of 7356 records information base (absolute size: 24.8 GB). Two lexically-matched phrases are expressed in an impartial North American vernacular by 24 expert entertainers (12 female, 12 male).

How to download the RAVDESS dataset in Python?

You can load the RAVDESS dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the RAVDESS dataset training subset in Python

How can I use RAVDESS dataset in PyTorch or TensorFlow?

You can stream the RAVDESS dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on the RAVDESS dataset with PyTorch in Python or train a model on the RAVDESS dataset with TensorFlow in Python.

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