[L2Ork-dev] Expression of interest in GSoC 2020

[Tsz Kiu Pang]

Hi all,

I am writing to express my interest in participating in GSoC with Purr
Data, in particular the project "Fake News Audio Library".

I have been using Pure Data for almost four years now, and would like to
further develop my skills by participating in GSoC this year.

Something about me
========
I am currently doing my last year of Master of Engineering (Electrical) at
the University of Melbourne.
I have solid foundations in DSP, and am experienced in implementing filters
for audio signals using C.
I have previously written some simple audio externals for pure-data after
learning from https://github.com/pure-data/externals-howto
which I think would be the right skill for this project.
I also have experience working with the Pure Data code base, and have
recently made a pull request:
https://github.com/pure-data/pure-data/pull/853

Demonstrating my skills
========
To further demonstrate my skills, I am planning to write an prototype
external to transform audio signal into a "warmer vinyl sound" in the
coming week.
However right now I am having trouble building purr-data from source, in
particular this error:
clang: warning: argument unused during compilation: '-fast'
[-Wunused-command-line-argument]
pdlua.c:45:10: fatal error: 'lua.h' file not found
#include <lua.h>
         ^~~~~~~
The problem seems to be that gcc is not able to locate the include file.
I have been attempting to solve this problem in the past hour, and would
continue doing so tomorrow
However it would be great if you could please point me in the right
direction.

Question regarding the project
========
In regards to the project "Fake News Audio Library", I would like to know
more about cross-referencing the "fake news".
Since we are dealing with fake news, I am assuming that there would not be
much reliable source (peer-reviewed journals, for example), and would have
to rely on sources such as:
https://www.oregonlive.com/music/2014/11/does_vinyl_really_sound_better.html
where it says the vinyl sound is "very mid-range-y and very warm", and
https://hydrogenaud.io/index.php?topic=73636.0
where it says the vinyl sound is "a prominent mid-bass with a slow decline
toward the high frequencies".
I am just wondering would this kind of referencing be sufficient enough as
a starting point?

Another question regarding the project is that how should the filters be
implemented?
Specifically, should they be implemented as externals written in C? Or
should they be implemented as abstractions patched in Pd?

Other projects
========
I am also interested in other projects such as "JIT-compiled Signal Graph
for the Audio Engine" and "Data Over Audio Messaging". However, upon
considerations, "Fake News Audio Library" seems to be the project which I
am most confident about. However, if other projects are more significant to
Purr Data or Pure Data, I am happy to look at those as well. Please let me
know what you think.

Time commitment
========
Since I am from Australia, where the summer in the US is our winter, so I
would only have approximately one and a half month in which I am able to
contribute full-time.
I have also expressed this issue last year and decided not to proceed with
the application due to the time commitment.
However this year I have a lighter study load as well as a better
understanding of the Pure Data code base, therefore I would be able to make
up the time overlapped with the semester.

>From the GSoC guideline, it seems like students have to spend at least 30
hours per week for 12 week, from 19/05 to 11/08, and the dates overlapped
with my semester are from 19/05 to 31/05 (14 days) and from 27/07 to 11/08
(another 14 days).
I would be able to contribute to this project for around 10 hours per week
during the semester time, and around 35 hours per week during my winter
holiday.
And if necessary, I can also start researching once I got accepted into the
project.
On top of these, I am confident with my knowledge in DSP and Pure Data, I
would be able to complete this project even with the limit of my time
commitment.

Thank you very much for your time.
Please let me know if you have further questions.

Kind regards,
Tsz-Kiu
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