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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Youtube-Dataset for Language Identification in Speech Signals

Research datakeyboard_double_arrow_right Dataset 31 Jul 2020Publisher:Zenodo
Authors: Draghici, Alexandra; Abeßer, Jakob; Lukashevich, Hanna;

doi: 10.5281/zenodo.3968292 , 10.5281/zenodo.3968291

Youtube-Dataset for Language Identification in Speech Signals

Abstract

Youtube-Dataset for Language Identification in Speech Signals - for scientific use only, for questions contact: jakob.abesser@idmt.fraunhofer.de Reference In case you use this dataset for your research, please cite Alexandra Draghici, Jakob Abeßer & Hanna Lukashevich: A Study on Spoken Language Identification using Deep Neural Networks, Proceedings of the Audio Mostly Conference 2020 Dataset The YouTube News Collection is a collection of videos from various Youtube news channels. We gathered data from channels like BBC news, France24, DW News, and Noticias Telemundo. - 135664 npy files (numpy matrices exported from Python) - each npy file includes a mel spectrogram (see below) of an audio file - the subfolders "0" - "5" encode the language id: 0 - English 1 - French 2 - German 3 - Greek 4 - Italian 5 - Spanish Audio Processing - mono, sample rate 22.05 kHz - mel spectrogram (librosa python package) - windows size 512 samples - hopsize 441 samples (20 ms) - 129 mel bands - file-level spectrogram are normalized to maximum of 1

Keywords

speech language identification

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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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