MATLAB Code Implementation for Short-Time Fourier Transform (STFT) with Audio Processing Capabilities

This document provides a comprehensive guide on implementing Short-Time Fourier Transform (STFT) using MATLAB for audio file analysis. STFT represents a fundamental signal processing technique that decomposes audio signals into sequential time windows, with each window undergoing Fourier transformation. Through STFT implementation, we can extract both frequency and temporal information from audio signals, facilitating deeper understanding of audio content characteristics. The MATLAB implementation typically involves creating overlapping window segments using functions like hamming() or hann(), followed by applying fft() to each segment to generate spectrograms.

Beyond STFT methodology, this guide delves into MATLAB's audio processing capabilities, specifically the audio file reading functionality. The audioread() function serves as a crucial tool for importing various audio formats (WAV, MP3, FLAC) and converting them into numerical arrays suitable for digital signal processing. We demonstrate proper implementation of audio parameter extraction including sampling frequency determination and normalization procedures, ensuring compatibility with subsequent STFT analysis. The code implementation covers essential preprocessing steps such as mono conversion and amplitude scaling.

In summary, this documentation presents a complete MATLAB workflow for audio analysis, combining STFT-based time-frequency decomposition with robust audio file handling capabilities. The integrated approach covers from initial audio data acquisition using audioread() to advanced spectral analysis through custom STFT implementation, providing practitioners with essential tools for speech processing applications. These techniques are particularly valuable for speech recognition, music analysis, and acoustic feature extraction tasks.