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ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2018
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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Vocal Imitation Set v1.1.3 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology

Authors: Bongjun Kim; Pardo, Bryan;

Vocal Imitation Set v1.1.3 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology

Abstract

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/). We expect that this dataset will help research communities obtain a better understanding of human's vocal imitation and build a machine understand the imitations as humans do. See https://github.com/interactiveaudiolab/VocalImitationSet for more information about this dataset and its latest updates. For citations, please use this reference: Bongjun Kim, Madhav Ghei, Bryan Pardo, and Zhiyao Duan, "Vocal Imitation Set: a dataset of vocally imitated sound events using the AudioSet ontology," Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018), Nov. 2018. Contact Info: - Interactive Audio Lab: http://music.eecs.northwestern.edu - Bongjun Kim bongjun@u.northwestern.edu | http://www.bongjunkim.com - Bryan Pardo pardo@northwestern.edu | http://www.bryanpardo.com

Related Organizations
Keywords

sound, audio information retrieval, vocal imitation, audio

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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