Plotting Spectrograms for Given WAV Files

This project demonstrates how to create spectrograms (spectral photographs) for given WAV audio files. The complete implementation includes program code and technical documentation. We provide detailed explanations of spectrogram concepts and their practical applications, helping readers better understand and utilize this audio analysis technique. The implementation typically involves loading WAV files using libraries like scipy.io.wavfile or MATLAB's audioread function, followed by Short-Time Fourier Transform (STFT) processing with adjustable window sizes (e.g., Hanning window) and overlap ratios. The package includes spectrogram examples for different audio types (speech, music, environmental sounds) with comparative analysis of their distinctive frequency characteristics and patterns. We discuss how to interpret spectrogram features for audio analysis and processing tasks, including practical techniques for audio enhancement and noise reduction using spectral subtraction algorithms. Furthermore, we demonstrate how to extract meaningful information from spectrograms through MATLAB's spectrogram function or Python's matplotlib.pyplot.specgram, covering parameter optimization for different audio resolutions. The documentation concludes with a comprehensive summary and provides research directions for advanced spectrogram applications in machine learning and signal processing.