In this video, we demistify and take a stab at understanding aliasing in audio signals. We start off the discussion by looking at how aliasing could occur in video signals by looking at the wagon wheel effect and how the aliasing pattern that you visually see can be applied to understand the concept of aliasing in audio signals. We force aliasing to occur in the digital domain by using the Nyquist programming language, draw a pattern, and derive a formula for predicting the aliased frequencies. We illustrate the process of sampling and see how a low sampling rate coupled with high frequencies can cause aliasing. We take the discussion towards real world observations of aliasing in square waves, and how to counter them manually using oversampling and downsampling.
Find the full playlist here: https://www.youtube.com/playlist?list=PLbqhA-NKGP6B6V_AiS-jbvSzdd7nbwwCw
Content:
0:00 Wagon wheel effect
2:08 Temporal aliasing
4:08 Forcing aliasing in Audacity
9:22 Sampling illustrated
11:24 Aliasing from square waves
13:56 Solutions to avoid aliasing
Tools:
Audacity (Free audio editing software) - https://www.audacityteam.org/download/
Sonic Visualiser (waveform/spectrum analyzer) - https://www.sonicvisualiser.org/download.html
Nyquist programming language reference manual - https://www.cs.cmu.edu/~rbd/doc/nyquist/
This video series explains the fundamentals of digital audio, how audio signals are expressed in the digital domain, how they're converted and transformed and the advantages of working with digital signals.
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