Get startedGet started for free

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.

This exercise is part of the course

Machine Learning for Time Series Data in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the stft function
____

# Prepare the STFT
HOP_LENGTH = 2**4
spec = ____(audio, hop_length=HOP_LENGTH, n_fft=2**7)
Edit and Run Code