A comparison of high precision F0 extraction algorithms for sustained vowels

Perturbation analysis of sustained vowel waveforms is used routinely in the clinical evaluation of pathological voices and in monitoring patient progress during treatment. Accurate estimation of voice fundamental frequency (F0) is essential for accurate perturbation analysis. Several algorithms have...

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Bibliographic Details
Published in:Journal of speech, language, and hearing research Vol. 42; no. 1; pp. 112 - 126
Main Authors: Parsa, V, Jamieson, D G
Format: Journal Article
Language:English
Published: United States 01.02.1999
Subjects:
Algorithms
Fundamental Frequency
Humans
Models, Biological
Noise
Noise - adverse effects
Phonetics
Speech Acoustics
Speech Pathology
Speech Production Measurement
Speech Synthesis
Voice Disorders - diagnosis
Voice Quality
Vowels
ISSN:1092-4388
Online Access:Get full text
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Summary:Perturbation analysis of sustained vowel waveforms is used routinely in the clinical evaluation of pathological voices and in monitoring patient progress during treatment. Accurate estimation of voice fundamental frequency (F0) is essential for accurate perturbation analysis. Several algorithms have been proposed for fundamental frequency extraction. To be appropriate for clinical use, a key consideration is that an F0 extraction algorithm be robust to such extraneous factors as the presence of noise and modulations in voice frequency and amplitude that are commonly associated with the voice pathologies under study. This work examines the performance of seven F0 algorithms, based on the average magnitude difference function (AMDF), the input autocorrelation function (AC), the autocorrelation function of the center-clipped signal (ACC), the autocorrelation function of the inverse filtered signal (IFAC), the signal cepstrum (CEP), the Harmonic Product Spectrum (HPS) of the signal, and the waveform matching function (WM) respectively. These algorithms were evaluated using sustained vowel samples collected from normal and pathological subjects. The effect of background noise and of frequency and amplitude modulations on these algorithms was also investigated, using synthetic vowel waveforms.
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ISSN:1092-4388
DOI:10.1044/jslhr.4201.112