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    <responseDate>2026-10-11T18:33:11Z</responseDate>
    <request verb="GetRecord" identifier="oai:data.mendeley.com/k47yd3m28w.4" metadataPrefix="oai_dc">https://data.mendeley.com/oai</request>
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        <record>
            <header>
                <identifier>oai:data.mendeley.com/k47yd3m28w.4</identifier>
                <datestamp>2020-01-31T14:21:16Z</datestamp>
            </header>
            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Ballesteros L, Dora Maria</dc:creator>
    <dc:title>H-Voice: Fake voice histograms (Imitation+DeepVoice)</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This data set consists of (6672) histograms of original voice recordings and fake voice recordings obtained by Imitation [1, 2] and Deep Voice [3]. The histograms provided in this dataset can be used to train a machine learning system to classify original and fake voice recordings obtained with the imitation and Deep Voice algorithms.

Each directory has the following composition:
-- corrupted images have been fixed --
Training_fake: 2088 histograms of fake voice recordings (2016 with Imitation and with 72 Deep Voice)
Training_original: 2020 histograms of original voice recordings 
Validation_fake: 864 histograms of fake voice recordings (all with Imitation)
Validation_original: 864 histograms of original voice recordings 
External_test1: 760 histograms (380 original + 380 fake with Imitation)
External_test2: 76 histograms (4 original + 72 fake with Deep Voice)

References:
[1] DM Ballesteros L, JM Moreno A. Highly transparent steganography model of speech signals using Efficient Wavelet Masking. Expert Systems with Applications 39 (10), 2012, 9141-9149, https://doi.org/10.1016/j.eswa.2012.02.066
[2] DM Ballesteros L, JM Moreno A. On the ability of adaptation of speech signals and data hiding, Expert Systems with Applications 39 (16), 2012, 12574-12579, https://doi.org/10.1016/j.eswa.2012.05.027
[3] S.O. Arik, M. Chrzanowski, A. Coates, G. Diamos, A. Gibiansky, Y. Kang, X. Li, J. Miller, A. Ng, J. Raiman, S. Sengupta, M. Shoeybi. Deep Voice: Real-time Neural Text-to-Speech. 2017. https://arxiv.org/abs/1702.07825</dc:description>
    <dc:subject>Computer Vision</dc:subject>
    <dc:subject>Speech Processing</dc:subject>
    <dc:subject>Machine Learning</dc:subject>
    <dc:contributor>Rodriguez, Yohanna Patricia</dc:contributor>
    <dc:contributor>Renza, Diego</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/k47yd3m28w.4</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/k47yd3m28w.4</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/k47yd3m28w</dc:relation>
    <dc:date>2020-01-31T14:21:16Z</dc:date>
</oai_dc:dc></metadata>
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