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In signal processing and related disciplines, aliasing is an effect that causes different signals to become indistinguishable (or aliases of one another) when sampled. It also refers to the distortion or artifact that results when the signal reconstructed from samples is different from the original continuous signal. When audio is downsampled improperly, high frequencies will turn into lower ones and the audio will sound extremely distorted. It's a great proxy for what happens to performance data when it's improperly sampled. Hodgson, J. (2020, 14. August). The "Sound " of Performance Monitoring, Part 2: Aliasing. Aternity. https://www.aternity.com/blogs/the-sound-of-performance-data-part-2/ |
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Original audio signal with full bandwidth.
Sample rate: 44,100 - file size: 128,000 bytes + wav header |
Reducing the sample rate by 8 produces an aliasing effect.
Sample rate: 5,512.5 - file size: 16,000 bytes + wav header |
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Original audio signal with reduced bandwidth (2.5 kHz).
Sample rate: 44,100 - file size: 128,000 bytes + wav header |
Now, reducing the sample rate not produces an aliasing effect. Can you hear the difference? Sample rate: 5,512.5 - file size: 16,000 bytes + wav header |
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There is an infinite number of aliases for every sampled frequency. Any sine wave is indistiguishable from an infinite number of sine waves after sampling. We force aliasing to occur an inharmonic roughness in the audio signal. Akash Murthy. (2020, 5. Mai). 4. Understanding Aliasing - Digital Audio Fundamentals [Video]. YouTube. https://www.youtube.com/watch?v=91PKZllbgds |
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