A) Experiment of Loudness estimation

This program conducts an auditory experiment using the method of magnitude estimation. The goal is to determine the parameters (a and b) of Stevens' Power Law, S=bP^a (Stevens, 1957, 1962), which relates loudness (S, in sones) and sound pressure (P, in dynes/cm²). The stimulus used is Gaussian white noise with 9 different levels of sound pressure: N₀=0, ±5, ±10, ±15, ±20 dB relative to the sound pressure level of the reference stimulus. Each level is presented 3 times, resulting in a total of 27 trials in the experiment.

 

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B) Experiment of Brightness estimation

This program conducts a visual experiment using the method of magnitude estimation. The goal is to determine the parameters (a and b) of Stevens' Power Law, B=bL^a (Stevens, 1957, 1962), which relates Brightness (B) and Luminance (L). In this experiment, circles are used as visual stimuli with 9 different luminance levels. Each level is presented 3 times, resulting in a total of 27 trials. In each trial, pairs of stimuli are presented, where the stimulus on the left is always the reference, and its luminance remains constant throughout the experiment.

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C) Estimating the auditory Critical Bands

 

The discovery of critical bands in hearing (Fletcher, 1940), from which it is inferred, through exclusively behavioral methods, the existence of multiple auditory filters, each selectively sensitive to a limited band of temporal frequencies within the audible range, is a milestone in our understanding of the functional architecture of the Human Auditory System. This milestone is little known and highly unrecognized outside the fields of Sensory Psychophysics and Audition. The following program allows us to experimentally demonstrate the existence of these critical bands and measure their effective width. It is based on a replication of Fletcher's original masking experiment, where the auditory threshold of pure tones (signal) was measured in the presence of bandpass noises centered on the signal frequency and with different temporal frequency widths.

In this program, the subject must adjust the sound pressure level of the signal (pure tones of 500 Hz or 2000 Hz) by sliding the bar for each width of the mask noise.

 

 

D) Estimating the Human Audibility Curve

The Human Audibility Curve (HAC) is the best measure we have to assess the performance of the auditory system. The HAC represents auditory thresholds for pure tones as a function of their temporal frequency. Therefore, any auditory deficit will be reflected in the HAC. The program allows determining auditory thresholds for 8 temporal frequencies quickly using the adjustment method. Each bar corresponds to a pure tone, and the subject has to adjust the volume until the tone is just audible.

 

 

E) Estimating the Contrast Sensitivity Function

Similar to the HAC, the Contrast Sensitivity Function (CSF) is the best measure we have to assess the performance of the visual system. It represents contrast thresholds for targets or sinusoidal gratings as a function of the spatial frequency of each grating. The goal of the experiment is to experimentally determine the Contrast Sensitivity Function (CSF).

 

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F) Estimating the Disparity Sensitivity Function

The aim of this program is to determine the Disparity Sensitivity Function (DSF). The program presents 6 horizontal sinusoidal corrugations with spatial frequencies of 1, 2, 3, 5, 8, and 12 cycles/image spatially windowed by a 2D isotropic Gaussian function (i.e., Gabor functions). The 3D corrugations have been created using random dot stereograms and the anaglyph technique. To generate the points in the stereograms, Gaussians have been used in such a way that subpixel disparities (disparity < 1 pixel) can be achieved. On the other hand, the stereograms have been designed so that the points (Gaussians) do not overlap. To conduct the experiment successfully, it is necessary for the students to wear 3D glasses (glasses with a red filter and a green or blue filter). For the proper observation of the stereograms, the red filter of the glasses should be placed in front of the right eye.

 

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G) Colorimetry (download Matlab program)

The objective of this program is for students to practice the colorimetric characterization of lights. In the program, data can be entered from the table or selected by clicking on the graph below the table. The program calculates the most relevant indices (e.g., tristimulus values, chromaticity coordinates) for the CIE 1931, CIE 1976 (L* u* v*), and CIE 1976 (L* a* b*) systems. It also displays the CIE 1931 and CIE 1976 (L* u* v*) chromaticity diagrams, representing light (Wyszecki & Stiles, 1982).