Spent a few days researching psychoacoustics and sound localisation to understand all the cues (5 of them, will talk more about them later!). Started working with an HRIR dataset (a dataset containing sound measurements from left and right ears of a mannequin from different directions, showing how ear shape and angles affect sound. the single most important cue in sound localisation). First wrote a function to plot raw left and right impulses, then ITD (time difference b/w ears). Then used Fourier transform to break impulses into frequency domain graphs showing magnitudes of particular frequencies, then the ILD (level difference). I was stuck here because the graph didn’t match my expectations at all (a very interesting problem too, check my reddit post: https://www.reddit.com/r/DSP/comments/1weg1dk/why_are_hrirhrtf_magnitude_differences_between/), until a person on reddit explained it, after which I also switched to a symmetrical HRIR dataset (SADIE II instead of Meta SS2). To visualise it better, I also created a heatmap of left/right ears, ILD, and left/right averages. Understanding this through different types of graphs and analysing them, recognising quirks, understanding what they meant was very interesting. Attaching pictures of the heatmaps, raw impulses, ITD, ILD curves :)