Detail publikace

Comparison of Different Kinds of Long-Time Spectra of Voice Estimated by Modified Linear Prediction to Distinguish Speakers

SIGMUND, M.

Originální název

Comparison of Different Kinds of Long-Time Spectra of Voice Estimated by Modified Linear Prediction to Distinguish Speakers

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper deals with two kinds of long-time spectra of speech estimated by the linear prediction approach. The standard approach usually used in short-time analysis was modified in two ways to achieve the long-time effect - either autocorrelation coefficients (AC) or predictive coefficients (PC) were averaged over a period of 2 minutes. The spectra were computed using order of prediction from 6 to 22 and evaluated in terms of diversity for a group of 17 speakers. To distinguish speakers, the most appropriate frequencies seem to be around 1010 Hz (AC averaged) or around 340 Hz (PC averaged).

Klíčová slova

Speech signal, long-time spectrum; linear prediction; distinction of voices

Autoři

SIGMUND, M.

Vydáno

10. 10. 2019

Nakladatel

Romanian Academy, IEEE, EURASIP

Místo

Bucharest

ISBN

978-1-7281-0983-1

Kniha

Proceedings of the 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD) “SpeD 2019”

Strany od

1

Strany do

6

Strany počet

6

URL

https://ieeexplore.ieee.org/document/8906615

BibTex

@inproceedings{BUT159592,
  author="Milan {Sigmund}",
  title="Comparison of Different Kinds of Long-Time Spectra of Voice Estimated by Modified Linear Prediction to Distinguish Speakers",
  booktitle="Proceedings of the 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD) “SpeD 2019”",
  year="2019",
  pages="1--6",
  publisher="Romanian Academy, IEEE, EURASIP",
  address="Bucharest",
  doi="10.1109/SPED.2019.8906615",
  isbn="978-1-7281-0983-1",
  url="https://ieeexplore.ieee.org/document/8906615"
}