Lecture 10 Experiment 2
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Transcript of Lecture 10 Experiment 2
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Lecture 10
Experiment 2
Martin Giese
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What you should remember
1. Function of the middle ear
2. Traveling wave theory
3. Audibility function
4. Loudness perception
5. Masking
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What you should learn today
1. Programming of stimuli in MATLAB
2. Data analysis
3. Details about the experiments
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Programming the Experiments
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Playsound
“High-level” function that plays a sinusoidal sound :
Playsound(f, A, t) plays sinusoidal tone with
frequency with frequency f and amplitude A for t seconds
Playsound(f, A, t, An, fn, Bn) plays sinusoidal tone with band pass background noise with mid frequency fn and band width +/-Bn
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Randomization
Example: Randomize conditions for 3 different frequencies (f1, f2, f3) and 2 different amplitudes Aij per frequency
Systematic proceeding:
1. Design matrix: 2 x 3
f1 f2 f3
A11
A12
A21
A22
A31
A32
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Randomization
2. Build equally shaped matrices for A and f
f1 f2 f3
Mf = f1 f2 f3
MA = A31
A32
A21
A22
A12
A12
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Randomization
3. Cast matrices into vectors:
Mf = Mf(:); MA = MA(:);
4. Build a random integer vector with # of conditions:
cond_index = randperm(length(Mf));
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Randomization
5. Address MA and Mf through this index: MA(cond_index(n)) (Amplitude of trial n)
Mf(cond_index(n)) (Frequency of trial n)
6. Loop over all trials:
for n=1:length(cond_index), ….. some function dependent on MA(cond_index(n)) and Mf(cond_index(n)) …..end;
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Reading In Key Presses
Example:
Check whether the key “a” or “l” has been pressed. If yes, print the letter, otherwise
ignore the key press.
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Reading In Key Presses
function key_demo(); % initializationret_strg = ‘‘;
% wait for a valid key presswhile strcmp(ret_strg, {'a', 'l'}) == 0, disp('Enter String.‘); ret_strg = getchar;end; % actions for admissible letters a and l if strcmp(ret_strg, 'a') == 1, disp('A');elseif strcmp(ret_strg, 'l') == 1, disp('L');end;
Simple example function
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Data Analysis
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Data Analysis
• Thresholds from probability data: – 50% threshold – Cool (optional): fit logistic threshold function
• Thresholds directly from adjustment methods / stair case
• Statistics for comparing thresholds: – t-test (pairwise comparisons) if enough items;
watch for (de)pendent measures !– non-parametric test for few items– ANOVA (next lecture)
• Extremely cool (idea for final project):run 2AFC experiment and estimate d’
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Data Analysis
Correction of the level
• Problem: test difference between 2 AFs • Given: N threshold values for K values
of the frequency {Akn} and {Akn}• Possibilities:
– t-test (pairwise comparisons) K independent tests
– Better: ANOVA (next lecture !)
How can we combine the results from K independent tests?
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Data Analysis
P(single test significant even though H0 true) <
P(single test non-significant if H0 true) >= 1-
Tests independent
P(all K tests non-significant if H0 true) >= (1- K
P(at least one out of the K tests significant if H0 true)
< 1 - (1- K = eq
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Data Analysis
Equivalent significance level for K independent tests:
eq = 1 - (1- K
= 1 - (1- eq1/K
For large K:
eqK (“Bonferoni correction”)
Example:
K = 4eq = 5 % = 1.27 %
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Experiments
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Method of Constant Stimuli
• Frequencies: 30, 500, 2k, 10k, 18k Hz
• Pilot: for each frequency regime find out approximately the threshold and set up 5 amplitudes around this value
• 20 repetitions
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Method of Limits
• Frequencies: 30, 500, 2k, 10k, 18k Hz
• Pilot: for each frequency regime find out approximately the threshold
• Ascending block: Start always with a stimulus that Ss don’t hear; increase by factor 1.2 until they hear; store result and start next trialDescending block: start with stimulus that Ss hear a decrease by factor 1.2 until they don’t hear stimulus any more
• 10 repetitions
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Staircase Method
• Frequencies: 30, 100, 200, 500, 1k, 2k, 5k, 10k, 15k, 18k Hz
• Pilot: for each frequency regime find out approximately the threshold
• Steps; multiply / divide by 1.2
• Cross threshold 8 times before next trial starts
• 5 repetitions
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Equal Loudness Contours
• Frequency of reference stimuli: 1000 Hz
• Test frequencies: 50, 100, 200, 500, 1k, 3k, 5k, 10k Hz
• 3 different amplitudes of the reference: low / medium / high
• Adjust amplitude of the test stimulus as to match loudness of reference
• 5 repetitions
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Difference Thresholds
• Frequency of reference stimulus: 200 Hz
• Test 5 different amplitudes of the reference in the regime between very low and (conveniently) high amplitudes
• Measure for each amplitude difference thresholds using a method of constant stimuli
• 15 repetitions for the method of constant stimuli
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Masking I
• Mask: narrowband noise with frequency 400 +/- 45 Hz
• Test frequencies: 100, 250, 400, 1k, 2k Hz
• Method of constant stimuli
• Trials with and without mask
• No time delay !
• 15 repetitions per condition
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Masking II
• Mid frequency of mask and test tone 400 Hz; bandwidth +/- 45 Hz
• 5 different time delays: 0, 50, 100, 200 ad 500 ms
• Method of constant stimuli
• Trials with and without mask
• 15 repetitions per trial