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?
- Source separation
- 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.