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RUJZL, M.; SIGMUND, M.
Original Title
Depersonalization of Speech Using Speaker-Specific Transform Based on Long-Term Spectrum
English Title
Type
WoS Article
Original Abstract
This paper introduces a novel approach for hiding personal information in speech signals. The proposed approach applied a transform warping function, which is obtained from a long-term linear prediction spectrum individually for each speaker. The depersonalized speech was compared with the often used technique based on vocal tract length normalization. The proposed approach performs wider manipulation of fundamental frequency and provides higher intelligibility by 5% in clean speech and by 8% for signal-to-noise ratio 5 dB. It also significantly alters the derived glottal pulses, making them difficult to use for personality analysis. Speech intelligibility index and glottal pulse distortion are new aspects in the field of voice depersonalization.
English abstract
Keywords
Speech depersonalization, long-term spectrum, voice transformation, depersonalized speech evaluation
Key words in English
Authors
RIV year
2024
Released
15.12.2023
Publisher
Czech Technical University in Prague
Location
Prague
ISBN
1210-2512
Periodical
Radioengineering
Volume
32
Number
4
State
Czech Republic
Pages from
523
Pages to
530
Pages count
8
URL
https://www.radioeng.cz/fulltexts/2023/23_04_0523_0530.pdf
BibTex
@article{BUT186825, author="Miroslav {Rujzl} and Milan {Sigmund}", title="Depersonalization of Speech Using Speaker-Specific Transform Based on Long-Term Spectrum", journal="Radioengineering", year="2023", volume="32", number="4", pages="523--530", doi="10.13164/re.2023.0523", issn="1210-2512", url="https://www.radioeng.cz/fulltexts/2023/23_04_0523_0530.pdf" }