Raw and post-processing data for using auditory models to mimic human listeners in reverse correlation experiments from the fastACI toolbox

Description: The current dataset provides all the stimuli (folder ../01-Stimuli/), raw data (folder ../02-Raw-data/) and post-processed data (../03-Post-proc-data/) used in the Forum Acusticum 2013 paper titled "Using auditory models to mimic human listeners in reverse correlation experiments from the fastACI toolbox" by the same authors. In this paper, we replicated the tone-in-noise experiment by Ahumada et al. (1975) but using an artificial listener instead of collecting data from real participants. The behavioural data were mimicked using an artificial listener based on 'king2019' (King et al., 2019) as a front-end model using a template-matching decision to indicate whether a 500-Hz tone was (or not) present in each of the noisy trials. This study offers a step-by-step guide of how can be an artificial listener integrated into fastACI.

Use these data: Download all these data, locate them in a local directory of your computer. If you have MATLAB and you downloaded a local copy of the fastACI toolbox (open access at: https://github.com/aosses-tue/fastACI) you can recreate the figures of our paper. After downloading and initialising the toolbox (type 'startup_fastACI;', without quotation marks in MATLAB), run the script g20230501_FA_Artificial_listener_paper_figs.m (provided in this dataset) and follow the instructions on the screen to generate one of the four study figures. This script calls the function publ_osses2023b_FA_figs.m from the toolbox.