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Grace’s Status Report for 2/15/25

This week, I worked on creating the rhythm detection algorithm. We first practiced by simply writing into a midi file, using the mido library in python, and then uploading the output into musescore so we could see what the sheet music generation looked like. 

We are trying to get the bare bones aspect of the project working, so we did a few different recordings, including the metronome alone, someone playing a D on the flute with the metronome in the background and no other sound, and then someone playing a D on the flute with some background noise (people talking). This helps us test with just detecting a note with the clear recording, but also experiment with noise suppression, which Shivi is working on. 

(what the isolated signals for the metronome and the flute note look like) 

After analyzing what these frequencies look like after doing a fourier transform on them, I isolated the signal by using a filter to filter out all other frequencies than the pitch of the note played and calculated the duration of the notes, using the inputted bpm. However, with audio recordings, there tends to be a lot of variation in the sound quality, creating a lot of peaks within the wave. This originally made my code think there were multiple different notes being played since I was trying to calculate it by the peaks. After analyzing the signal further, I migrated to using 20% of the max amplitude to use as a threshold to calculate the duration of a note. I then transcribed this into a midi file and uploaded it to musescore to look at the results. Though it is still not accurate for the rhythm, I am hopeful that this will be working soon and plan on using a sliding window filter in future testing to reduce the number of peaks and noise. 

(what is currently being transcribed to musescore, should just be a signal note so will need to reassess my threshold value) 

My current progress is on schedule. This next week I hope to get the rhythm detection accurately working for a whole note, quarter note, and a half note for the same note at the very least. Hopefully, I will be able to detect switches in notes soon as well.

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Team Status Report for 02/08/25

As we had proposal presentations this week, we worked hard on finishing up our slides, ensuring that they were done far enough in advance that Ankit, our TA, would be able to give us feedback on our schedule. Here, Ankit had mentioned the possibility of converting our hardware systems (like the microcontroller of an arduino) be done solely in software instead, as it would function a lot faster. We are currently considering this option: Since we would ideally like to convert this system into real time, it would be best for faster processing. However, this could result in changes on how we approach tasks, like rhythm detection. We are planning on reaching out to Ankit again to talk this over further. 

Last week, we also meet with Professor Dueck and other musicians to discuss what our project looks like and how the music department could contribute to our project, such as allowing us to work in her studio to test the flutes in a relatively noiseless environment, which would be best for a bare bones working project. Additionally, she connected us with Professor Almarza, who will be helping us find some flutists to help test our project.

After this, we experimented with looking at some straight tone flute signals and seeing how this pitch would appear in Matlab. This is to get more insight in getting a bare bones project up and working.

Currently, our most significant risk would be switching the project and having unforeseen consequences and then having to backtrack to the hardware idea, which is a little more fleshed out due to past project references. These risks could be managed by discussing this further with our TA and staff, like Professor Sullivan. As such, this might pose a possible change to the existing design, specifically the system spec, to help with the speed. Overall, we feel that we are on track and excited to see where our project tasks us as well as work collaboratively with CMU musicians to get their feedback throughout the process.

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Grace Status Report for 02/08/25

This week, we primarily focused on finishing our proposal slides. We made sure to get them done in advance so our TA, Ankit, would be able to give us feedback on our schedule and our parts. In class, we listened to the different presentations and gave feedback. It was helpful to see all the presentations in our section, since most of them also related to signal processing, and it gave us inspiration on how we might approach handling our signals from the flute. 

During the presentation, Ankit gave us some insightful feedback on whether we should continue using hardware for the signal processing, which would entail using a microcontroller and possibly an op amp, or move to entirely software. It is true that most likely using solely software would help with the real time aspect of the project, but I’m not entirely sure how this would end up translating for the rhythm detection, which I am tasked with. Originally, our plan was to include a blinking light on a physical device/hardware and that would allow people to maintain a steady bpm (essentially providing a metronome). With moving to software, we could implement a similar feature on the web application but I’m not sure how accurately we would be able to detect rhythm since our original plan was to time it with how long it would take to send to the web app via serial. I would definitely need to do some more research on how to record and detect rhythm. 

Our plan from here on out is to divide into our scheduled task as we are currently on schedule, with Shivi and I primarily working on the signal processing side of the project and Deeya doing research and beginning to work on the web app. Our first next step would be reaching out to Ankit, or any other specialist TA in signal processing, to ask which would work best for us in terms of hardware vs software.

Looking forward, I hope to have a solid game plan and have implemented the bare bones of the rhythm detection for the signal processing and work on integrating this information with Shivi to put into our midi file within the next two weeks. Furthermore, we hope to meet with some flutists from CFA and get their feedback on how they would like the website to look and how they would like the machine to function.