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SIGMUND, M.
Original Title
Comparison of Different Kinds of Long-Time Spectra of Voice Estimated by Modified Linear Prediction to Distinguish Speakers
Type
conference paper
Language
English
Original Abstract
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).
Keywords
Speech signal, long-time spectrum; linear prediction; distinction of voices
Authors
Released
10. 10. 2019
Publisher
Romanian Academy, IEEE, EURASIP
Location
Bucharest
ISBN
978-1-7281-0983-1
Book
Proceedings of the 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD) “SpeD 2019”
Pages from
1
Pages to
6
Pages count
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" }