Welcome to Project SonicSpectrum! This repository contains code dedicated to analyzing audio files using Fast Fourier Transforms (FFT) and visualizing the frequency spectrum in a sinusoidal graph. Created by Joshua Mukisa & Emmanuel Asiimwe, this project aims to provide insights into the frequency components of audio signals, with a particular focus on the famous track "Pirates of the Caribbean - He's a Pirate.mp3".
This repository contains code dedicated to applying Fast Fourrier Transforms (FFT) to an audio file, and visualising it in a sinusoidal graph.
Audio File Name: Pirates of the Caribbean - He's a Pirate.mp3
FFT (Fast Fourier Transform) is an algorithm used to compute the discrete Fourier transform efficiently.
The Discrete Fourier Transform (DFT) is mathematically represented as follows:
In this expression:
-
$X_k$ represents the$k$ -th element of the DFT output. -
$x_m$ denotes the$m$ -th element of the input sequence. -
$e^{-i \frac{2\pi k m}{n}}$ is the complex exponential term, where$e$ is the base of the natural logarithm,$i$ is the imaginary unit, and$\pi$ is the mathematical constant pi.
Additionally,
To get started with Project SonicSpectrum, follow these steps:
- Clone this repository to your local machine.
- Ensure you have the necessary dependencies installed, including librosa, numpy, matplotlib, and pandas. (necessary dependencies can be found in the requirements.txt file)
- Open the Jupyter Notebook file "SonicSpectrum.ipynb" to explore the code and analyze audio data.
- Customize the code as needed for your own audio files or projects.
- Joshua Mukisa
- Emmanuel Asiimwe
- File Name: Pirates of the Caribbean - He's a Pirate.mp3
Contributions to Project SonicSpectrum are welcome! If you have ideas for improvements, new features, or bug fixes, feel free to open an issue or submit a pull request.