(compMus2) Spectral Quiz Review

For Wednesday’s (12/10) quiz over spectral processing, review the previous posts on intro to spectral processing, the Fourier transform, phase vocoding, and convolution.

Important Concepts

The quiz is not limited to the listed items below, but these concepts will go a long way towards helping you master the important material.

Intro to Spectral Processing

  • Audio domains (time, frequency)
  • Converting between time and frequency domain
  • Missing, or unspecified elements in each domain
  • The difference between time domain processes and frequency domain processes, with the ability to name some processes in each domain. (This last concept is drawn from all the posts, along with previous work we’ve done in class.)

The Fourier Transform

  • What the theorem states (i.e., the part about any periodic signal could be represented….)
  • The different implementations of the FT (FT, DFT, STFT, FFT), and how these implementations relate to each other
  • The FFT, specifically relating to the computational benefits of using an FFT size that is a power of 2
  • The Uncertainty Principle as it applies to the FT
  • FFT parameters (size, window type, bin, frame, overlaps, hop size)
  • The relationship of the FFT size to the number of frequency bands being analyzed
  • Problems with the FFT (FT): periodic, spacing of bands, time/frequency trade-off

Phase Vocoding

  • What audio manipulations/processes can be accomplished with phase vocoding
  • How time compression/expansion works with phase vocoding (also, be able to compare this to granular synthesis)
  • How pitch shifting works with PV.
  • How you overcome (to some degree) the time/frequency trade-off


  • Convolution as a fundamental process in digital audio processing
  • The musical uses of convolution
  • Be able to describe in words the basic process of convolution
  • Implementation of convolution (using spectral processing)
  • The Law of Convolution, and its usefulness for implementing convolution
  • Understanding how convolution works to filter signals and to apply reverberation.


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