ep-413 DSP – week 4


Audio Signal Processing Course: https://www.coursera.org/course/audio

By Xavier Serra and Julius O. Smith

This is a free course offered by Stanford. It starts at the beginning of October. I will be taking the course and would be happy to help you if you are interested in taking it too.

Pd weekend 2014: Katja Vetter Microphone design: http://libguides.lib.siu.edu/puredata

Part I – Pitch detection

How would you construct an ‘Autotune’ effect that works in real time?  The first requirement is accurate pitch detection:

Frequency domain:

FFT and STFT: Find frequencies where the signal has greatest energy. Tradeoff between frequency and temporal resolution. Moderate latency.

Max examples: https://reactivemusic.net/?p=11202

Also look at the builtin Max tutorials on the fft~ and pfft~ objects

3rd party Max/Pd objects:

DSP code

Time domain:

Zero crossing: Measure the period of waves by counting rate of zero crossings. Doesn’t work with complex waveforms.

Max objects: fzero~ and zerox~

Autocorrelation: Compare a signal with a time shifted copy of itself.  Low latency but CPU intensive. Can be improved by using lower sample rates and other tweaks. (Helmholtz)

Example patches: https://reactivemusic.net/?p=17169

(note: gbr.yin~ is a 3rd party object from IRCAM, but is built into Max)

Pd examples from Katja Vetter: (helmholtz~ external)

We also looked at Katja’s new app: InstantDecomposer. If you would like to try this patch, please contact me. I will need to get permission from Katja.

Wavelet transform:
Other methods:
  • phase locked loop
  • human pitch matching (what is the latency?)
  • Neural networks?
  • Statistical methods (pattern matching)?

Part II – Prototyping

Muse development case study: https://reactivemusic.net/?p=16187


Next week we will listen to your music from the future.