Audio Analysis and Visualization

This project is a Python script for analyzing audio files and visualizing the top musical notes detected in the audio. It utilizes the Fast Fourier Transform (FFT) to convert audio from the time domain to the frequency domain and identifies prominent musical notes based on their amplitudes.

Features

• Audio analysis and note detection.
• Visualization of the top musical notes in the order they are played.
• Visualization of the audio waveform.

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.x

Usage

1. Clone this repository to your local machine:

   git clone https://github.com/gtrtuugii/WAV-Notes-Converte.git

2. Change into the project directory:

   cd WAV-Notes-Converter

3. Run the script with your audio file:

   python3 fft_wav.py your_audio_file.wav

   Replace your_audio_file.wav with the path to your audio file.

4. The script will analyze the audio, detect musical notes, and display visualizations.

Configuration

You can configure the script by modifying the following parameters in main.py:

• FPS: Frames per second for audio analysis.
• FFT_WINDOW_SECONDS: Window size in seconds for FFT analysis.
• To determine the number of top musical notes to detect during the analysis you can adjust the num parameter when calling the find_top_notes function based on your specific analysis requirements.

# Example: Detect the top 5 notes
top_notes = find_top_notes(fft, num=5, xf=xf)

Example

Acknowledgments

• numpy - Numerical computing library for Python.
• matplotlib - Plotting library for Python.
• scipy - Scientific computing library for Python.

Feel free to contribute to this project by opening issues or pull requests.