Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2
datasets available to search
ShareScore release 0.9.0
Dataset results
2 results for “Multichannel audio”
Auditory Scene Analysis dataset (Multichannel universal sound separation & polyphonic audio classification)
<p>We constructed a new dataset for <strong>multichannel universal sound separation</strong> and <strong>polyphonic audio classification</strong> tasks.</p> <p>We constructed a new dataset for multichannel USS and polyphonic audio classification tasks. The proposed dataset is designed to reflect various conditions, including moving sources with temporal onsets and offsets. For foreground sound sources, signals from 13 audio classes were selected from open-source databases (Pixabay and FSD50K, Librispeech, MUSDB18, Vocalsound). These signals were resampled to 16 kHz and pre-processed by either padding zeros or cropping to 4 seconds. Each sound source has a 75% probability of being a moving source, with speeds ranging from 0 to 3 m/s. The dataset features between 2 to 4 foreground sound sources, along with one background noise from the diffused TAU-SNoise dataset with a signal-to-noise ratio (SNR) ranging from 6 to 30 dB. The simulations were conducted using gpuRIR. Room dimensions were set to a width and length between 5 and 8 meters, and a height between 3 and 4 meters, with reverberation times ranging from 0.2 to 0.6 seconds. These parameters were sampled from uniform distributions. We simulated spatialized sound sources using a 4-channel tetrahedral microphone array with a radius of 4.2 cm. The procedure for dataset generation and details about class configuration and durations of audio clips are provided in the paper. This dataset poses a significant challenge for separation tasks due to the inclusion of moving sources, onset and offset conditions, overlapped in-class sources, and noisy reverberant environments.</p> <p>The procedure for dataset generation and details about class configuration and durations of audio clips are provided in the paper. This dataset poses a significant challenge for separation tasks due to the inclusion of moving sources, onset and offset conditions, overlapped in-class sources, and noisy reverberant environments.</p>
Comparison of 2D and 3D Multichannel Audio Rendering Methods for Hearing Research Applications using Technical and Perceptual Measures - Impulse Responses and Scene Recordings
<p>This database contains recordings of impulse responses (IRs.zip) and virtual acoustic scenes (scenes.zip), with different 2D and 3D multichannel loudspeaker rendering methods. This upload contains conplementary data to [1].</p> <p>The virtual acoustic scenes are a 'concert' of an orchestra with approximately 60 primary sound sources [2] in a reverberant room, a 'speech' scene with a single talker in the same room, and a 'street' scene with static and moving sound sources.</p> <p>Recordings were performed with a G.R.A.S. 45BB Head and Torso Simulator (Kemar) placed in the center of the loudspeaker array in the lab, with ears at 1.60 m height. Recordings include the left and right ear channel. The simulator was equipped with large anthropometric pinnae of type KB5001. All recordings are provided for each rendering method that was applied in the study [1].</p> <p>Impulse responses were recorded using sine sweeps [3], sampling frequency was 44100 Hz. The impulse responses were truncated to 1.2 s. The scenes were recorded with a sampling frequency 44100 Hz.</p> <p> </p> <p>Files are named with the following convention:</p> <p>filetype_scene_renderingmethod_source.[mat/wav]</p> <p> </p> <p>References:</p> <p>[1] M. Gerken, V. Hohmann, G. Grimm, "Comparison of 2D and 3D Multichannel Audio Rendering Methods for Hearing Research Applications using Technical and Perceptual Measures," Acta Austica 2024, in press.</p> <p>[2] C. Böhm, D. Ackermann, and S. Weinzierl, "A Multi-channel Anechoic Orchestra Recording of Beethoven's Symphony No. 8 op. 93," Journal of the Audio Engineering Society, vol. 68, no. 12, pp. 977–984, Jan. 2021, doi: 10.17743/jaes.2020.0056.</p> <p>[3] A. Farina, "Simultaneous Measurement of Impulse Response and Distortion with a Swept-Sine Technique," in Audio Engineering Society Convention 108, Feb. 2000. [Online]. Available: http://www.aes.org/e-lib/browse.cfm?elib=10211</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.