Rounding of the glottal source waveform for breathy voice

1. 
   Open SpeechTool/Ztool, then use the File menu to open ‘br01.wav’ (‘c:\ztool\br01.wav’ – on the LRC machines, it’s ‘r:\ztool\br01.wav’).
   

2. 
   Play the signal as many times as you wish and rate how breathy the voice is on a scale of 1 to 5, with 5 being the most breathy. Record your rating for this signal. So, the row of data for this signal will look like this:
   

br01.wav 3 (or whatever)

3. 
   Toward the end of the string of buttons at the top, you will see one called ‘CPP’. Bugging this button will run a program that estimates how periodic the signal is by measuring the degree of harmonic organization in its narrow band spectrum. The very last number that the program gives you is called “Mean CPPS”. Larger CPPS values indicate a higher degree of harmonic organization – i.e., most of the energy is at harmonically related frequencies, indicating a more periodic signal. Consequently, small values of CPPS should be associated with less periodic (breathier) voices. Write this number down in the same row as your breathiness rating. Your row of data should now look something like this:
   

br01.wav 3 0.71

4. 
   Do the same thing for the remaining nine signals. In your table of results, you should have your breathiness rating (1-5) and a CPPS value for each test signal.
   

5. 
   Below is a table of breathiness ratings for each signal.
   

br01.wav 8.22

br02.wav 5.21

br03.wav 2.12

br04.wav 2.86

br05.wav 5.33

br06.wav 1.51

br07.wav 7.94

br08.wav 3.42

br09.wav 4.07

br10.wav 4.87
These are very much like the breathiness ratings (BR) that you made, except that these ratings are averages from a panel of 21 listeners doing pretty much what you did. (These values vary from ~1.5 to ~8.2 instead of 1-5, but this doesn’t matter.) Copy these breathiness ratings into a new column of the table you created. So, each row in your table will have, in this order: (1) the name of the signal, (2) your breathiness rating, (3) the CPPS value from Ztool, and (4) the average rating from the 21-listener panel. Use Word to create a file called ‘brXXXX.txt’ (where ‘XXXX’ is the last 4 digits of your WIN – or any random string of numbers, e.g., ‘br1598.txt’) in the ztool folder with all of these numbers in it (filename, your BR, CPP, and panel BR – for all 10 signals). The 1^st line should look something like this:
br01.wav 3 0.71 8.22
All 10 lines need to be in exactly this format; e.g., you want “0.71” NOT “0.71 dB”.
In Word, set the font to Courier and use the space bar only, not the Tab key. SAVE YOUR FILE AS PLAIN TEXT (File>Save as>Choose plain text, using the name ‘brXXXX.txt’; e.g., ‘br4598.txt’. (If Word asks you about “text encoding”, just leave it at the Windows default setting.)

6. 
   The last step is to measure correlations between: (1) your BR and the panel BR (columns 2 and 4), (2) your BR and CPPS (columns 2 and 3), and (3) the panel BR and CPPS (columns 3
   

and 4). A correlation is a measure of the strength of the relationship between two sets of numbers.¹ The easiest way to measure a correlation happens to be the most arcane, but it’s not that bad:

1. 
   Hold down the Windows key (the one with the flag-looking thing on it) and hit ‘R’.
   
2. 
   Type ‘cmd’ into the text box that pops up.
   
3. 
   Put your cursor in the black window that appears and type:
   

c:

cd c:\ztool’
(LRC people: Use r: instead of c:)

4. 
   Let’s assume you want to measure the correlation between your BR (col 2) and CPPS (col 3). Type this arcane thing:
   

.\tcor brXXXX.txt 2 brXXXX.txt 3 (measure the correlation between col 2 and col 3)

.\tcor brdata.txt 3 brdata.txt 4

correlation between your BR and the panel BR _______ _______

correlation between your BR and CPP _______ _______

correlation between the panel BR CPP _______ _______

1. 
   How well do your breathiness ratings agree with the panel ratings? Note that the more important measure of the strength of a relationship is rsq (r²) rather than r: for example, an r value of 0.8 is not 80% of perfect, but an rsq value of 0.8 is 80% of perfect.
   

2. 
   How well do the CPPS measures predict your breathiness ratings?
   

3. 
   How well do the CPPSmeasures predict the panel breathiness ratings?
   

4. 
   Why is the correlation between breathiness ratings and CPPSnegative? (If you’re not sure, see footnote 1).
   

5. 
   What do you make of all this? For example, is there any advantage to using this measure of periodicity measure in place of your own subjective estimate?
   

6. 
   Look at the figures on the last two pages of this document and read the description at the top of the page. Pick the two spectra that seem to show the most harmonic organization, and the two spectra that seem to show the least harmonic organization. (These are subjective judgments, so there are no right and wrong answers. The signal you pick for the most harmonic organization should be very clean looking, with most of its energy at harmonically related frequencies; vice versa for the signal with the least harmonic organization.) Record your results below, along with the panel breathiness rating and the CPPSvalue for each signal:
   

Signal with the most harmonic organization

7. 
   Last question: Do the voices that you judged to have the most harmonic organization tend to be among the signals with: (a) the lowest breathiness ratings and/or (b) the largest CPPSvalues?