Formant frequency estimation of high-pitched vowels using weighted linear prediction.
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.
Department of Signal Processing and Acoustics, Aalto University, P.O. Box 13000, FI-00076 Aalto, Finland. paavo.alku@aalto.fi
Paavo
P
Alku
Jouni
J
Pohjalainen
Martti
M
Vainio
Anne-Maria
AM
Laukkanen
Brad H
BH
Story
D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D002675:Child, Preschool; D003198:Computer Simulation; D005260:Female; D005931:Glottis / Q000033:anatomy & histology / Q000502:physiology*; D006801:Humans; D016014:Linear Models; D008297:Male; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated; D010699:Phonation; D010700:Phonetics; D010898:Pitch Perception; D011312:Pressure; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013061:Speech Acoustics; D013068:Speech Production Measurement; D013997:Time Factors; D014827:Vocal Cords / Q000502:physiology; D014833:Voice Quality