Omkar2118/datasets huggingface dataset:
FSL4
Full name: Freesound Loops 4k

The **FSL4** dataset contains ~4000 user-contributed loops uploaded to Freesound. Loops were selected by searching Freesound for sounds with the query terms loop and bpm, and then automatically parsing the returned sound filenames, tags and textual descriptions to identify tempo annotations made by users. For example, a sound containing the tag 120bpm is considered to have a ground truth of 120 BPM.

Source: [https://zenodo.org/record/3685832](https://zenodo.org/record/3685832)
Image Source: [https://archives.ismir.net/ismir2016/paper/000195.pdf](https://archives.ismir.net/ismir2016/paper/000195.pdf)
SimSceneTVB Learning
Full name: SimSceneTVB Learning

SimSceneTVB is a dataset of 600 simulated sound scenes of 45s each representing urban sound environments, simulated using the simScene Matlab library. The dataset is divided in two parts with a train subset (400 scenes) and a test subset (200 scenes) for the development of learning-based models.
Each scene is composed of three main sources (traffic, human voices and birds) according to an original scenario, which is composed semi-randomly conditionally to five ambiances: park, quiet street, noisy street, very noisy street and square. Separate channels for the contribution of each source are available. The base audio files used for simulation are obtained from Freesound (https://freesound.org) and LibriSpeech (http://www.openslr.org/12). The sound scenes are scaled according to a playback sound level in dB, which is drawn randomly but remains plausible according to the ambiance.

Source: [https://zenodo.org/record/3248703](https://zenodo.org/record/3248703)
Image Source: [https://hal.archives-ouvertes.fr/hal-01078098v2/document](https://hal.archives-ouvertes.fr/hal-01078098v2/document)

Introducing paper: SimSceneTVB Learning
SimSceneTVB Perception
Full name: SimSceneTVB Perception

**SimSceneTVB Perception**  is a corpus of 100 sound scenes of 45s each representing urban sound environments, including: 6 scenes recorded in Paris, 19 scenes simulated using simScene to replicate recorded scenarios, 75 scenes simulated using simScene with diverse new scenarios, containing traffic, human voices and bird sources.The base audio files used for simulation are obtained from Freesound (https://freesound.org) and LibriSpeech (http://www.openslr.org/12).

Source: [https://zenodo.org/record/3248734](https://zenodo.org/record/3248734)
Image Source: [https://hal.archives-ouvertes.fr/hal-01078098v2/document](https://hal.archives-ouvertes.fr/hal-01078098v2/document)

Introducing paper: SimSceneTVB Perception
Sound Events for Surveillance Applications
Full name: Sound Events for Surveillance Applications

The **Sound Events for Surveillance Applications** (SESA) dataset files were obtained from Freesound. The dataset was divided between train (480 files) and test (105 files) folders. All audio files are WAV, Mono-Channel, 16 kHz, and 8-bit with up to 33 seconds. # Classes: 0 - Casual (not a threat) 1 - Gunshot 2 - Explosion 3 - Siren (also contains alarms).

Source: [https://zenodo.org/record/3519845](https://zenodo.org/record/3519845)
Image Source: [https://labs.freesound.org/datasets/](https://labs.freesound.org/datasets/)

Introducing paper: Sound Events for Surveillance Applications (Version 1.0.0)
VocalImitationSet
Full name: VocalImitationSet

The **VocalImitationSet** is a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (https://freesound.org/), which were curated based on Google's AudioSet ontology (https://research.google.com/audioset/).

Source: [https://zenodo.org/record/1340763](https://zenodo.org/record/1340763)
Image Source: [https://www.researchgate.net/publication/332799163_VOCAL_IMITATION_SET_A_DATASET_OF_VOCALLY_IMITATED_SOUND_EVENTS_USING_THE_AUDIOSET_ONTOLOGY](https://www.researchgate.net/publication/332799163_VOCAL_IMITATION_SET_A_DATASET_OF_VOCALLY_IMITATED_SOUND_EVENTS_USING_THE_AUDIOSET_ONTOLOGY)