A deliverable for John, to show that I can deliver.
Take into account that before this project, I had never touched Matlab.
Well, once I did, using a program Adam had made, I entered data and it spit out a polar plot.
But really nothing of any use relating to this project.
Last night I completed this first working beta version on my listening test software.
There are still some things to change i.e. how it exports test data and biasing the sliders to the middle. Otherwise, it is just a bit slow and clunky. This is because every time you move a slider, it recalculates the mix of tracks, adds them and normalises them before playing from the same sample. Initial listens show some very strange, interesting and unpredicted results. As such, I need the software to be reviewed by someone who actually understands how Matlab works to a good level.
My advances have been great in a very short space of time, but there is still a mountain to go!
So here the is format of the listening test as far:
The listener has to go through 7 genres of music, listening to each track at least twice. The listener for each track, is to move the appropriate slider, one to find the best sound, and once to find the loudest sound for each genre. The listener is also to put in their sex and age, and save the answers between each genre. I haven't finished how saving and exporting data works yet. For this, I need Adam or Bruce.
It has been a learning curve, the last 24 hours. But here it is.
I aim to optimise it better, change the save behaviour, and make it much prettier. But it is a deliverable beta, put together in roughly 10 hours.
I am pretty chuffed.
The data recorded is fully quantitative, in that numerical values between 0 and 1 are chose, by listeners who don't know what they are listening to i.e. without deception by still blind.
The next step from a data perspective, is to polish up the sample choice, and look at the crest factor of each sample at given times in the sample. Then once listening test data is back, determine the difference in crest factor for the highest and lowest populated data points.
I think it is in fact the effect on crest-factor as I originally thought, that determines perceived loudness in these basic listening tests. I believe that greater THD makes lower mid and bottom end more perceptible, by masking the top end clarity of the music. I believe that this perceived extension in bass is what clubbers want, and you can hear it in the sample variations when listening to a 2.1 speaker system. I haven't tried headphones yet. I think the next step is more tests with the better quality samples, and multiple NLDS.
Really, testing needs to happen with people whose ears have gone into 'protect mode', with the 3piece system seizing up a little. Unfortunately, there is no way the ethics police will allow that. So I may need to look into modelling that mathematically. I will also need access to whatever the military has on this behaviour.
My aim by the end of the week is to have beta V2 together, and to have done a reasonably hardcore literature review on crest factor and the ears internal protection system.
Woop!
Below is a link to the folder including the Matlab embed of my beta.
In the folder above, the first test interface is here.
No comments:
Post a Comment