Dataset Open Access
Dataset used in COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations
Xavier Favory;
Konstantinos Drossos;
Tuomas Virtanen;
Xavier Serra
This dataset consists of two hdf5 files that contain pre-computed log-mel spectrograms that have been used to to train audio embedding models. The dataset is split into a training set and a validation set containing respectively 170793 and 19103 spectrogram patches with their accompanying multi-hot encoded tags from a vocabulary of 1000 tags provided by Freesound users.
More details can be found in "COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations" by X. Favory, K. Drossos, T. Virtanen, and X. Serra. The code is available at this GitHub repository.
License:
This dataset is derived from content from the Freesound collection. All sounds are released under Creative Commons (CC) licenses from either CC0, CC-BY, CC-S+, or CC-BY-NC. We attribute authors of all the sounds used in the dataset and provide their corresponding licenses in the attributions.txt file.
| Name | Size | |
|---|---|---|
|
attributions.txt
md5:f8caf5d6797fab41d5309fb982c0a9e9 |
23.1 MB | Download |
|
spec_tags_top_1000
md5:b75e6a7e0fb96cad034c523c4cf9f804 |
6.6 GB | Download |
|
spec_tags_top_1000_val
md5:af3b62f3105b516e93ac7ad4c4227028 |
742.5 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 649 | 649 |
| Downloads | 2,298 | 2,298 |
| Data volume | 9.8 TB | 9.8 TB |
| Unique views | 598 | 598 |
| Unique downloads | 878 | 878 |
- Publication date:
- June 9, 2020
- DOI:
-
- Keyword(s):
- audio representation learning deep neural network co-aligned autoencoders contrastive loss audio classification spectrograms
- License (for files):
- Other (Attribution)