MATLAB Code Implementation for Reading WAV Files

Processing audio files in MATLAB is a common task, especially when analyzing WAV format audio. This guide demonstrates how to read WAV files and displays both time-domain waveforms and frequency-domain characteristics.

Reading WAV Files MATLAB provides the `audioread` function to load WAV files. The function returns the audio data and its sampling rate. The audio data is typically a two-dimensional array where each column represents a channel (mono or stereo). The sampling rate indicates the number of samples per second, which is a crucial parameter for subsequent time-domain analysis. The implementation involves simple function calls: [audio_data, sample_rate] = audioread('filename.wav')

Plotting Time-Amplitude Graph (Time-Domain Analysis) With audio data and sampling rate obtained, you can calculate the time axis. The time axis is generated by dividing the number of sample points by the sampling rate, mapping discrete sample points to actual time values. Use the `plot` function to create amplitude-versus-time waveform graphs. For stereo audio, typically you need to plot left and right channels separately or calculate their average. Code implementation includes creating time vectors: time = (0:length(audio_data)-1)/sample_rate; followed by plotting with plot(time, audio_data)

Fourier Transform (Frequency-Domain Analysis) To analyze frequency components of audio signals, apply Fourier transform to time-domain signals. MATLAB's `fft` function performs Fast Fourier Transform to obtain frequency-domain representation. By taking the magnitude spectrum of the transform results and using the sampling rate to calculate the frequency axis, you can plot spectrum graphs. Typically, logarithmic scale (such as dB units) is applied to the spectrum to enhance visualization, particularly for audio signals where this clearly shows energy distribution across different frequencies. Implementation involves: fft_result = fft(audio_data); freq_axis = (0:length(fft_result)-1)*sample_rate/length(fft_result); followed by magnitude calculation and plotting

In summary, MATLAB's built-in functions make audio file reading and analysis straightforward and efficient. Time-domain waveforms reveal amplitude variations, while frequency-domain analysis uncovers signal frequency composition, together providing comprehensive perspectives for audio processing tasks.