Voice Signal Processing for Machine Learning: Comparative Analysis of Fourier and Wavelet Transforms for Speaker Isolation

This work provides a concise comparative analysis of Fourier and Wavelet transforms, the most commonly used signal decomposition methods for audio processing tasks. It also discusses metrics for evaluating speech intelligibility, with the goal of guiding machine learning engineers in choosing and fine-tuning a decomposition method for a specific model.