2022 Projects
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Swiftie Bot
By Franklin Liu, Darin Vu, Lucas Bai
Project Description: A robot that classifies songs as either Taylor Swift or non-Taylor Swift. The robot labels Taylor Swift as a positive and non-Taylor Swift as a negative. When a positive song is played, the robot dances by moving its arms up and down and also lights up and blinks its eye. When a negative song is played the arms stop moving and the light turns off.
Auto Harmonizer
By Leo Gong, Yashnil Saha, Aiden Mathew
Project Description: Using a user interface, the user either inputs a midi file with the melody or allows the program to compose a melody, and chords will be generated to accompany the melody. The chords can be customized using several parameters chosen by the user. The program also produces a backing drum track including a snare drum, bass drum, and hi-hat. The technique of voice leading is utilized to determine which inversion of each chord best fits the melody. This project is designed for music beginners who have trouble creating harmonies for their melodies.
Insta-Score
By Theo Fong, Tim Fan, Justin Zhang, Oliver Zheng
Project Description: Our project will use spectrogram analysis and machine learning to transcribe a music file, usually classical or pop, instantly into sheet music. It will also identify the chord progressions for any accompanists to the performer such as pianists or guitarists. If possible, the program will use machine learning to distinguish between instruments. The goal of our project is to provide a convenient way to access sheet music without any pay, and also provide basic musical analysis.
Mood Lobe
By Jonathan Deng, Jeffrey Lin, Vaidehi Karve
Project Description: There are two aspects to our project—both with an overarching theme of sonification.
The first project is called Mood Lobe. An electroencephalogram (EEG) will be used to scan the user’s brain waves and detect their emotions and physical movements. Through signal processing, it will modify the waves according to the user’s behavior and produce an auditory output. A visual response will also be created depending on the emotions that are detected.
The second project, PLANETS, is a cooperative agreement between NASA and PLANETS partners, including USGS (United States Geological Survey), NAU Center for Science Teaching and Learning (CSTL), Museum of Science Boston, EiE, and WestEd. We specifically worked on a project helping to universalize the project to support youth experiencing physical disabilities, starting with the Remote Sensing Unit. Students would investigate different minerals using their visual spectra, while our project allows blind and low-vision youth to experience the activity; we sonified the spectra of the minerals, using four different approaches to create audio files.
Project Poster Board (USGS and NASA)
Project Presentation (EGG)-Part 1
Project Presentation (EGG)-Part 2
Project Presentation (Planets-USGS and NASA)-Part 1
Project Presentation (Planets-USGS and NASA)-Part 2
Harmonia
By Iris Lo, Alina Shah, Angelina Wang
Project Description: The computer will play a progressive scale and ask the user to repeat after it. It will recognize when the user sings off pitch and record the highest and lowest note sung comfortably. Keeping in mind the user’s vocal range, the program will determine which vocal part is suitable and provide appropriate songs.
FRAIM
By Siddhant Upadhyay, Chris Zhang, Max Messer
Project Description: Our project will read in an image that the user will upload. This image will be an up close image of a human face, kind of like a portrait photo. Then, our software program will recognize the most dominant emotion the person in the image is displaying, and create a chord progression that matches the emotion.