For the past two weeks I have mainly been working on refining the timing algorithm and working with Ben and Mathias on integration to turn the three subsystems into one complete solution.
I started setting up the raspberry pi and put ubuntu on the system. The next step for this would be to install the code and make sure I can get a working output. Also making sure that the audio interfaces are able to connect to the pi correctly.
I also have been working with Ben on the data output from the audio processing subsystem in order to improve my section. During the interim demo, we were able to show the system working to some degree, but we did notice that there were spikes in the audio which corresponded with a new note. We’ve been working together to combine these in order to make my timing algorithm more accurate and there has been some success so far.
I have also spent time working on the final report. I have began doing tests on my subsystem in regards to the quantitative requirements and worked with Ben and Mathias to determine what our testing environments are going to be. We decided to test on beginner, medium, and advanced pieces of sheet music which we classify based on things such as chords and speed. We also will be testing based on audio in an isolated environment and a real world environment such as a normal room.
After this testing I can take a look on the results and see what optimizations I need to make for the final demo and will give us good data for the final presentation.
Overall I am very happy with how the project is progressing and I am on track to be demo ready by finals week.
For the upcoming week I plan on finishing the final presentation and continue to work with Ben and Mathias on optimizing my algorithm and system integration.
Some new knowledge I learned during this project is signal processing algorithms such as dynamic time warping and how to record audio in a recording studio. These were both very foreign topics to me as I am mostly a very hardcore software person. Some learning strategies I used to accomplish this is by first reading about the theory online and then just jumping in and trying to do something. I noticed that by throwing myself at a problem I am able to learn way faster than by just reading or watching videos on how to do something. For the dynamic time warping, watching videos were really good at learning how it worked fundamentally, but by getting my hands dirty with the data, I was able to see how it worked in the real world and some of the challenges there are for dealing with relatively messy and unideal data.