Institute for Response-Genetics (e.V.)

Chairman: Prof. Dr. Hans H. Stassen

Psychiatric Hospital (KPPP), University of Zurich

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CORR — Correlation analyses of voice parameters, scatter plots

Computes correlation coefficients (such as Pearson product-moment or Spearman rank coefficient) between recording days (repeated assessments), experimental conditions, or the 2 corresponding probands in a matched-pairs design. As an option, this program generates scatter plots thereby including the 2 regression lines y = y(x) and x = x(y). Such plots give a visual impression of the range of inter-individual differences and of the stability of individual parameter scores over time: all points lying along the diagonal indicate perfect reproducibility, whereas, in the case of less perfect reproducibility, the angle between the 2 regression lines is inversely proportional to the correlation between the 2 recordings under comparison. The specificity of parameters can be identified in a scatter plot through the shape of the point "cloud": a "sausage"-shaped cloud along the diagonal indicates a high specificity of the underlying parameter, whereas all points clustering in a compact ball is an indicator of low specificity.

            Specificationlist:        CORR
            ------------------------------
            I4 PROT                      0  Default-value
            I4 PLOT                      0  Default-value
            I4 PMAX                      0  Default-value
            I4 LPRT                      6  Default-value
 
            01 PROT Controls output to display/printer
            02 PLOT Controls graphic output
            03 PMAX Specifies maximum number of plot pages
            04 LPRT Logical unit number of plot-device
            05 DEMO Examples that illustrate program function
 
 
            - PROT = 0: No print output
                   = 1: Simple statistics
                   = 2: Detailed analyses
 
            - PLOT = 0: No plot output
                   = 1: Scatter plots, no regression lines
                   = 2: Scatter plots, single regression line
                   = 3: Scatter plots, two regression lines
 
            - PMAX = q: Maximum number of plot pages
                   = 0: Unlimited number
 
            - LPRT = q: Logical unit number of plot-device (standard=6;
                        valid numbers are 46-96)
 
 
            - DEMO: Correlation between recording days, experimental conditions
 
           

Example

 
            &&START GSELECT=Normative speech study zurich: ages 20-25 (study 600)
             STUD=600,MODE=1,STAT=2,AMIN=20,AMAX=25,PROT=1,RSET=1,PROZ=10
             POPU=AGE20-25
              ?
            &&START GSELECT=Normative speech study zurich: ages 30-35 (study 600)
             AMIN=30,AMAX=35,RSET=0
             POPU=AGE30-35
              ?
            &&START CORR=Normative speech study zurich (study 600)
             PROT=1,PLOT=3,LPRT=66
            &&START GSELECT=Normative speech study zurich: ages 20-25 (study 600)
             STUD=600,MODE=2,ATAG=1,AMIN=20,AMAX=25,PROT=1,RSET=1,PROZ=10
             POPU=AGE20-25
            &&START GSELECT=Normative speech study zurich: ages 30-35 (study 600)
             AMIN=30,AMAX=35,RSET=0
             POPU=AGE30-35
            &&START CORR=Normative speech study zurich (study 600)
             PROT=1,PLOT=3,LPRT=66
 
           
vSpacer voxFig26
Fig. 26: Voice sound characteristics possess a distinct "individuality" that allows one, for example, to identify persons on the phone very quickly without speaking explicitly about the identity of the speaker. In fact, voice sound characteristics have a strong biological component in the range of 80% or higher. This biological predisposition is also replected by a significant correlation between body height and men vocal pitch.
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