Spectrograms of heartbeat audio
Spectral engineering is one of the most common techniques in machine learning for time series data. The first step in this process is to calculate a spectrogram of sound. This describes what spectral content (e.g., low and high pitches) are present in the sound over time. In this exercise, you'll calculate a spectrogram of a heartbeat audio file.
We've loaded a single heartbeat sound in the variable audio.
Den här övningen är en del av kursen
Machine Learning for Time Series Data in Python
Interaktiv övning med praktiskt arbete
Testa den här övningen genom att slutföra den här exempelkoden.
# Import the stft function
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# Prepare the STFT
HOP_LENGTH = 2**4
spec = ____(audio, hop_length=HOP_LENGTH, n_fft=2**7)