The TAU Sound Events and Speech Privacy Preservation Dataset is a collection of audio data used in the work "Adversarial Representation Learning for Robust Privacy Preservation in Audio" by S. Gharib, M. Tran, D. Luong, K. Drossos, and T. Virtanen. The dataset is created by merging subsets of the Freesound 50k Dataset (FSD50K) and the LibriSpeech corpus. Both FSD50K and LibriSpeech are licensed under the Creative Commons license. The dataset contains of ~5000 one-second sound event samples with or without speech content provided in WAV and NumPy array format (approximately half of the samples contains speech). The creation of the dataset ensures an equal number of samples for male and female speakers across each sound event class. The sound event classes included in this dataset are: dog barking glass breaking gun shot cough slam applause dished pot pan toilet flush cat meowing doorbell crying drill Please check the README for better understanding of the dataset.

2023