SIM—simultaneous inverse filtering and matching of a glottal flow model for acoustic speech signals

Matthias Fröhlich; Dirk Michaelis; Hans Werner Strube

doi:10.1121/1.1379076

SIM—simultaneous inverse filtering and matching of a glottal flow model for acoustic speech signals

The Journal of the Acoustical Society of America ◽

10.1121/1.1379076 ◽

2001 ◽

Vol 110 (1) ◽

pp. 479-488 ◽

Cited By ~ 29

Author(s):

Matthias Fröhlich ◽

Dirk Michaelis ◽

Hans Werner Strube

Keyword(s):

Flow Model ◽

Speech Signals ◽

Inverse Filtering ◽

Glottal Flow

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Glottal inverse filtering by combining a constrained LP and an HMM-based generative model of glottal flow derivative

Speech Communication ◽

10.1016/j.specom.2018.07.002 ◽

2018 ◽

Vol 104 ◽

pp. 113-128

Author(s):

Akira Sasou

Keyword(s):

Generative Model ◽

Inverse Filtering ◽

Glottal Flow

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Estimation of the glottal flow from speech pressure signals: Evaluation of three variants of iterative adaptive inverse filtering using computational physical modelling of voice production

Speech Communication ◽

10.1016/j.specom.2018.09.005 ◽

2018 ◽

Vol 104 ◽

pp. 24-38 ◽

Cited By ~ 2

Author(s):

Parham Mokhtari ◽

Brad Story ◽

Paavo Alku ◽

Hiroshi Ando

Keyword(s):

Physical Modelling ◽

Inverse Filtering ◽

Voice Production ◽

Glottal Flow

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Parameterization of a computational physical model for glottal flow using inverse filtering and high-speed videoendoscopy

Speech Communication ◽

10.1016/j.specom.2017.11.007 ◽

2018 ◽

Vol 96 ◽

pp. 67-80 ◽

Cited By ~ 5

Author(s):

Tiina Murtola ◽

Paavo Alku ◽

Jarmo Malinen ◽

Ahmed Geneid

Keyword(s):

Physical Model ◽

High Speed ◽

Inverse Filtering ◽

Glottal Flow

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Estimation of amplitude features of the glottal flow by inverse filtering speech pressure signals

Speech Communication ◽

10.1016/s0167-6393(98)00004-1 ◽

1998 ◽

Vol 24 (2) ◽

pp. 123-132 ◽

Cited By ~ 12

Author(s):

Paavo Alku ◽

Erkki Vilkman ◽

Anne-Maria Laukkanen

Keyword(s):

Inverse Filtering ◽

Glottal Flow

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An Algorithm to Estimate Anticausal Glottal Flow Component from Speech Signals

Nonlinear Speech Modeling and Applications - Lecture Notes in Computer Science ◽

10.1007/11520153_15 ◽

2005 ◽

pp. 338-343

Author(s):

Baris Bozkurt ◽

François Severin ◽

Thierry Dutoit

Keyword(s):

Speech Signals ◽

Flow Component ◽

Glottal Flow

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Parameterization of the Voice Source by Combining Spectral Decay and Amplitude Features of the Glottal Flow

Journal of Speech Language and Hearing Research ◽

10.1044/jslhr.4105.990 ◽

1998 ◽

Vol 41 (5) ◽

pp. 990-1002 ◽

Cited By ~ 4

Author(s):

Paavo Alku ◽

Erkki Vilkman ◽

Anne-Maria Laukkanen

Keyword(s):

Sound Pressure Level ◽

Sound Pressure ◽

Pressure Level ◽

New Method ◽

Inverse Filtering ◽

Voice Production ◽

Voice Source ◽

Volume Velocity ◽

Glottal Flow ◽

The Voice

A new method is presented for the parameterization of glottal volume velocity waveforms that have been estimated by inverse filtering acoustic speech pressure signals. The new technique, Parameter for Spectral and Amplitude Features of the Glottal Flow (PSA), combines two features of voice production, the AC value and the spectral decay of the glottal flow, both of which contribute to changes in vocal loudness. PSA yields a single parameter that characterizes the glottal flow in different loudness conditions. By analyzing voices of 8 speakers it was shown that the new parameter correlates strongly with the sound pressure level of speech.

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