Introduction to signal processing using FFT

A Fourier Transform takes a signal (usually acoustic or any sequence of data) and finds the frequencies that are dominant in the signal. For example: A pure middle 'C' note from piano.

Why is it important?

  1. Source separation
  2. Identifying emotions in voices.

So it's important for me as I am researching in emotion detection from speech.

FFT (Fast Fourier Transform) is a very efficient algorithm for computing the power spectrum (Fourier transform). The normal Fourier Transform is a O(N^2), whereas FFT is O( N log(N)).

So in this workshop I will show how FFT can be performed in real-time and I will show how human voices produce different power spectrum. I will also let the audience see what their own vocal profile looks like.

Date: 19/05/2017
Time: 16:00
Location: LB252

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