Estimation of the Voice Source from Speech Pressure Signals: Evaluation of an Inverse Filtering Technique Using Physical Modelling of Voice Production

2006 ◽  
Vol 58 (2) ◽  
pp. 102-113 ◽  
Author(s):  
Paavo Alku ◽  
Brad Story ◽  
Matti Airas
Keyword(s):  
Physical Modelling ◽  
Inverse Filtering ◽  
Voice Production ◽  
Voice Source ◽  
Filtering Technique ◽  
The Voice

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

1998 ◽  
Vol 41 (5) ◽  
pp. 990-1002 ◽  
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.

scholarly journals Estimation and Statistical Analysis of Human Voice Parameters to Investigate the Influence of Psychological Stress and to Determine the Vocal Tract Transfer Function of an Individual

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Puneet Kumar Mongia ◽  
R. K. Sharma
Keyword(s):  
Statistical Analysis ◽  
Transfer Function ◽  
Psychological Stress ◽  
Vocal Tract ◽  
Inverse Filtering ◽  
Human Voice ◽  
Filtering Technique ◽  
The Mean ◽  
The Relationship ◽  
The Voice

In this study the principal focus is to examine the influence of psychological stress (both positive and negative stress) on the human articulation and to determine the vocal tract transfer function of an individual using inverse filtering technique. Both of these analyses are carried out by estimating various voice parameters. The outcomes of the analysis of psychological stress indicate that all the voice parameters are affected due to the influence of stress on humans. About 35 out of 51 parameters follow a unique course of variation from normal to positive and negative stress in 32% of the total analyzed signals. The upshot of the analysis is to determine the vocal tract transfer function for each vowel for an individual. The analysis indicates that it can be computed by estimating the mean of the pole zero plots of that individual’s vocal tract estimated for the whole day. Besides this, an analysis is presented to find the relationship between the LPC coefficients of the vocal tract and the vocal tract cavities. The results of the analysis indicate that all the LPC coefficients of the vocal tract are affected due to change in the position of any cavity.

Estimating the voice source in noise

2012 ◽  
Author(s):  
Gang Chen ◽  
Yen-Liang Shue ◽  
Jody Kreiman ◽  
Abeer Alwan
Keyword(s):  
Voice Source ◽  
The Voice

The Voice

2019 ◽  
pp. 187-200
Author(s):  
Peter Townsend
Keyword(s):  
Signal Processing ◽  
The Other ◽  
Voice Production ◽  
Tone Quality ◽  
Electronic Sound ◽  
Electronic Signal Processing ◽  
Musical Evolution ◽  
The Voice ◽  
Individual Input ◽  
Electronic Signal

Voice and singing are fundamental to music. Scales and content reflect our personal culture. Something beautiful and inspiring to one person may be a boring cacophony to another. Viewing musical evolution from the perspective of culture is therefore varied and individual. Input from science is generally less obvious, except for changes generated from acoustics of buildings, broadcasting, and electronic sound equipment. Medical studies reveal how we form sounds and tone quality, and modern electronic signal processing shows the complexity of the harmonic content of singing. The changes between sweetness, harshness, carrying power, and so on, all depend on not just volume, but the fundamental note and its harmonics, plus all the other frequencies generated in our vocalization. One fundamental may have 50 or more other frequencies. This signal processing tool is invaluable for understanding voice production.

Vortex shedding and the voice source

2007 ◽  
Vol 121 (5) ◽  
pp. 3121-3121
Author(s):  
Michael S. Howe ◽  
Richard S. McGowan
Keyword(s):  
Vortex Shedding ◽  
Voice Source ◽  
The Voice
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