JOURNAL ARTICLE

Formant frequency estimation of high-pitched vowels using weighted linear prediction

Paavo AlkuJouni PohjalainenMartti VainioAnne-Maria LaukkanenBrad H. Story

Year: 2013 Journal:   The Journal of the Acoustical Society of America Vol: 134 (2)Pages: 1295-1313   Publisher: Acoustical Society of America

Abstract

All-pole modeling is a widely used formant estimation method, but its performance is known to deteriorate for high-pitched voices. In order to address this problem, several all-pole modeling methods robust to fundamental frequency have been proposed. This study compares five such previously known methods and introduces a technique, Weighted Linear Prediction with Attenuated Main Excitation (WLP-AME). WLP-AME utilizes temporally weighted linear prediction (LP) in which the square of the prediction error is multiplied by a given parametric weighting function. The weighting downgrades the contribution of the main excitation of the vocal tract in optimizing the filter coefficients. Consequently, the resulting all-pole model is affected more by the characteristics of the vocal tract leading to less biased formant estimates. By using synthetic vowels created with a physical modeling approach, the results showed that WLP-AME yields improved formant frequencies for high-pitched sounds in comparison to the previously known methods (e.g., relative error in the first formant of the vowel [a] decreased from 11% to 3% when conventional LP was replaced with WLP-AME). Experiments conducted on natural vowels indicate that the formants detected by WLP-AME changed in a more regular manner between repetitions of different pitch than those computed by conventional LP.

Keywords:
Formant Vocal tract Weighting Parametric statistics Mathematics Linear prediction Speech recognition Vowel Acoustics Computer science Statistics Physics

Metrics

82
Cited By
10.37
FWCI (Field Weighted Citation Impact)
47
Refs
0.98
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Citation History

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Phonetics and Phonology Research
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
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