Detail publikace

Depersonalization of Speech Using Speaker-Specific Transform Based on Long-Term Spectrum

RUJZL, M. SIGMUND, M.

Originální název

Depersonalization of Speech Using Speaker-Specific Transform Based on Long-Term Spectrum

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Speech depersonalization, long-term spectrum, voice transformation, depersonalized speech evaluation

Autoři

RUJZL, M.; SIGMUND, M.

Vydáno

15. 12. 2023

Nakladatel

Czech Technical University in Prague

Místo

Prague

ISSN

1210-2512

Periodikum

Radioengineering

Ročník

32

Číslo

4

Stát

Česká republika

Strany od

523

Strany do

530

Strany počet

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"
}