Estimation of the voice source from speech pressure signals: Evaluation of an inverse filtering technique using physical modelling of voice production

Paavo Alku, Brad Story, Matti Airas

Research output: Contribution to journalArticle

29 Scopus citations

Abstract

Objective: The goal of the study is to use physical modelling of voice production to assess the performance of an inverse filtering method in estimating the glottal flow from acoustic speech pressure signals. Methods: An automatic inverse filtering method is presented, and speech pressure signals are generated using physical modelling of voice production so as to obtain test vowels with a known shape of the glottal excitation waveform. The speech sounds produced consist of 4 different vowels, each with 10 different values of the fundamental frequency. Both the original glottal flows given by physical modelling and their estimates computed by inverse filtering were parametrised with two robust voice source parameters: the normalized amplitude quotient and the difference (in decibels) between the levels of the first and second harmonics. Results: The results show that for both extracted parameters the error introduced by inverse filtering was, in general, small. The effect of the distortion caused by inverse filtering on the parameter values was clearly smaller than the change in the corresponding parameters when the phonation type was altered. The distortion was largest for high-pitched vowels with the lowest value of the first formant. Conclusions: The study shows that the proposed inverse filtering technique combined with the extracted parameters constitutes a voice source analysis tool that is able to measure the voice source dynamics automatically with satisfactory accuracy.

Original languageEnglish (US)
Pages (from-to)102-113
Number of pages12
JournalFolia Phoniatrica et Logopaedica
Volume58
Issue number2
DOIs
StatePublished - Feb 1 2006

Keywords

  • Glottis
  • Inverse filtering
  • Physical modelling
  • Voice production

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Speech and Hearing
  • LPN and LVN

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