Building Machine Learning Systems with Python - Third Edition

Decomposing music into sine-wave components

Our plan is to extract individual frequency intensities from the raw sample readings (stored in X earlier) and feed them into a classifier. These frequency intensities can be extracted by applying the fast Fourier transform (FFT), which translates the wave signal into coefficients of its frequency components. As the theory behind FFT is outside the scope of this chapter, let's just look at an example to get an idea of what it accomplishes. Later on, we will treat it as a black-box feature extractor.

For example, let's generate two WAV files, sine_a.wav and sine_b.wav, which contain the sound of 400 Hz and 3,000 Hz sine waves, respectively. The aforementioned Swiss Army knife, sox, is one way to ...