Target detectability and left-right and near-far movement detectability
At the first appointment, we assessed target detectability in the presence of four interferers. For this purpose, we used a singleinterval 2-alternative-forced-choice paradigm with 50 trials. In half of the trials, a static target sound was present, while in the other trials only the four interferers were presented. Each interval had a duration of 3.1 s. On each trial, the task of the participants was to indicate whether they heard the target sound by pressing a button on the screen (“Yes” or “No”). Using a threshold criterion, pcorrect, of 90% detection accuracy, we divided the participants into groups that could (good performers, group 1+4 (N = 2, which is far from ideal regarding statistical analysis): mean pcorrect = 98%, standard deviation = 2.8%) or could not (poor performers, group 1+2 (N = 13): mean pcorrect = 64.8%, standard deviation = 15.1%) easily hear out the target sound.
Depending on the target detectability outcome, the movement detection thresholds were measured without (group 1+0, poor performers) or with (group 1+4, good performers) the four interferers. The procedure for measuring the detection thresholds was very similar to that in our previous study.9 On half of the trials, we simulated a moving target sound, whereas in the other trials the target sound remained static at the reference position (0°, 1 m). For the angular measurements, we randomized the direction of movement (towards the left or right), whereas for the radial measurements we always simulated a withdrawing (N-F) movement. In this manner, we ensured the same reference position (0°, 1 m) for both movement dimensions. To control the extent of the movement, we varied the velocity (in °/s or m/s) in the adaptive procedure. For the angular source movement measurements, the velocity ranged from 2 to 30°/s (starting value: 17.4°/s) across all tracks. For the radial source movement measurements, it ranged from 0.25 to 3.7 m/s (starting value: 1.74 m/s). The smallest step size was 2° or 0.25 m. The stimulus duration was constant (2.3 s), thus the amount of movement was proportional to the velocity. On each trial, the task of the participants was to indicate whether they heard a movement (independent of the direction) of the target sound or not by pressing a button on the screen (‘Yes’ or ‘No’). For the adaptive procedure, we used the single-interval adjustment-matrix method of Kaernbach.15 This procedure takes hits, misses, false alarms and correct rejections into account and in this way enables unbiased adaptive testing. A so-called payoff matrix determines the magnitude of the changes made to the adaptive parameter (in our case, the velocity) for each combination of stimulus and response. The adjustment factors that we used were -1 (hits), 1 (misses), 2 (false alarms) and 0 (correct rejections). For our measurements, we chose a desired target performance of t = 0.5. A run was terminated after 12 reversals, and the first four reversals were discarded from the analyses. A single run took 3-5 min to complete. Before the actual measurements, each participant completed two training runs with six reversals each, one with the OMNI condition and the other with the AUTO condition. The actual measurements were performed with the OMNI, AUTO and DIR conditions.
We estimated the detection thresholds by taking the arithmetic mean of the last eight reversal points of each measurement run. In this manner, we quantified the smallest displacement (in ° or m) of the target source that the participants were able to detect within the 2.3 s over which the movements occurred. In the following, we will refer to these thresholds as the minimum audible movement angle (MAMA) and minimum audible movement distance (MAMD) thresholds.
We carried out the L-R and N-F source movement measurements in separate blocks. Within these blocks, we tested the various conditions in randomized order. In total, we measured three LR thresholds and three N-F thresholds per listener (and thus 90 thresholds in total). We had to exclude the data from one participant because of problems with understanding the tasks.
Prior to the statistical analyses, we examined the distributions of the various datasets. According to Kolmogorov-Smirnov’s test, all datasets fulfilled the requirements for normality (all P > 0.05). We therefore used parametric statistical tests to analyze our data. Whenever appropriate, we corrected for violations of sphericity using the Greenhouse-Geisser correction.
Movement direction and number of concurrent sources
At the second appointment, all participants (the division of groups was removed) were asked to perform the two tasks in the virtual street environment, that is, indicating the movement direction of the target source and counting the number of concurrent sound sources. On each trial, we presented a random number of sounds (1-5) from random positions (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°). To keep the scene realistic, the vehicle sounds were placed a greater distance away from the listener (10-15 m) whereas the bike and pram sounds were closer (5 m). One of the sounds moved within the 15 s of stimulus presentation (±45°), while the others remained static. After the presentation, the participants had to press a button on a touch screen. The two tasks were administered using a graphical user interface that was visible during the whole stimulus presentation. The first task was to indicate the number of sound sources in the last trial. Here, buttons with numbers from 1-6 were provided (Figure 4A). The second task was to indicate in which direction the target source moved. For that purpose, eight buttons were provided containing arrows depicting different movement directions (Figure 4B).
Each of the blocks consisted of 24 trials, where task 1 (count the sound sources) and task 2 (indicate the movement direction) were equally distributed. The three HA conditions were tested in randomized order. This resulted in a total of 144 trials and a measurement time of about 1 hr. Data from one of the participants could not be used for the same reason as stated before (i.e. inability to understand the tasks).