Our project converts streamed audio signals from a mic to visual outputs in real time. We analyze the inputs through the use of Fourier Transformations which are an important part of digital signal processing.
We found the idea of Fourier transformation very intriguing since we are really interested in mathematics. The topic of audio and visual processing also excited us. We believe this project will be a service to the society where it would help the deaf people to get a portrayal of music and audio through visual signals.
Our project processes and visualizes external sound signals by using Fast Fourier Transformation. Through FFT, we are able to separate the component frequencies of a signal and assign bands of frequency to certain colors or other visuals in the output.
We captured external audio input through the microphone of the laptop which was stored as amplitude vs time signals. Using Fast Fourier Transformation (FFT), we converted these signals to power vs frequency signals thereby obtaining discrete frequencies. Based on the frequency range, we applied certain colors for certain ranges of frequency.
To begin with, this whole topic was new to us. We had to do a substantial amount of research before being able to start work. The mathematical aspect of FFT was also difficult to implement. Java graphs and graphics also took a lot of time to learn and code.
In a short time, we were able to learn, understand, and implement new difficult concepts. We met our goals and were able to constantly expand our ideas while extending our horizons. We were able to convert between two types of media. Also, we innovated something which will be of value to the community.
We learned a whole new concept of mathematics namely Fourier Transformation. We implemented this in programming using Fast Fourier Transformation. We gained experience in different Java aspects: Java GUI, audio streams, and graphs. The bare-bones of using git/GitHub. Finally, that any project is possible to complete in 33 hours with a positive attitude, motivation, and determination.
We would like to expand the visual output to a spectrogram while also optimizing the code for FFT. Also, We would love to incorporate VR to have a more complete "musical-color" transformation.
Laptop microphone, Java(without external APIs), JavaFX for GUI.
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