DMCA
Accurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound (1993)
Cached
Download Links
| Venue: | IFA Proceedings 17 |
| Citations: | 260 - 4 self |
BibTeX
@INPROCEEDINGS{Boersma93accurateshort-term,
author = {Paul Boersma},
title = {Accurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound},
booktitle = {IFA Proceedings 17},
year = {1993},
pages = {97--110}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
We present a straightforward and robust algorithm for periodicity detection, working in the lag (autocorrelation) domain. When it is tested for periodic signals and for signals with additive noise or jitter, it proves to be several orders of magnitude more accurate than the methods commonly used for speech analysis. This makes our method capable of measuring harmonics-to-noise ratios in the lag domain with an accuracy and reliability much greater than that of any of the usual frequency-domain methods. By definition, the best candidate for the acoustic pitch period of a sound can be found from the position of the maximum of the autocorrelation function of the sound, while the degree of periodicity (the harmonics-to-noise ratio) of the sound can be found from the relative height of this maximum. However, sampling and windowing cause problems in accurately determining the position and height of the maximum. These problems have led to inaccurate timedomain and cepstral methods for pitch detection, and to the exclusive use of frequency-domain methods for the determination of the harmonics-to-noise ratio.
Keyphrases
harmonics-to-noise ratio accurate short-term analysis fundamental frequency pitch detection several order exclusive use frequency-domain method cepstral method robust algorithm autocorrelation function periodic signal usual frequency-domain method periodicity detection acoustic pitch period relative height lag domain additive noise speech analysis cause problem
