Two analysis features I'd like to see
Posted: Mon Feb 23, 2015 12:11 am
Whether built into Audacity or as an add-on like Nyquist or whatever:
Blind Source (or Signal) Separation: Can pull apart a number of sources into discrete output signals, convolved into a single mono signal. Can be used to separate signal and noise, whether pseudo-random (pink, brown, thermal, etc.) noise, or multiple similar sources (one voice among many -- the "cocktail party effect").
Continuous wavelet transform: A method of spectral analysis far beyond FFT. Can develop an accurate time/frequency plot from signal for doing time selective filtering, artifact detection, all manner of signal/noise separation.
Both are available as code of various flavors, most common being Matlab. Both can be used as the basis for subtractive s/n reduction, or simply separation so one can use that as a decision making tool for what other analysis or alteration techniques to apply. I can help with describing what they do and how, and can assist with existing code location and code author assistance/advice, but I can't code for squat. Rather I can, but if you need anything newer than Apple ][ machine level programming or more general that SPSS automation, you'd best look elsewhere.
"No matter what you're trying to do, it's good to remember that just as weeds are plants you don't want, noise is signal you don't want." -- Karl Pribram (1919 - 2015)
Blind Source (or Signal) Separation: Can pull apart a number of sources into discrete output signals, convolved into a single mono signal. Can be used to separate signal and noise, whether pseudo-random (pink, brown, thermal, etc.) noise, or multiple similar sources (one voice among many -- the "cocktail party effect").
Continuous wavelet transform: A method of spectral analysis far beyond FFT. Can develop an accurate time/frequency plot from signal for doing time selective filtering, artifact detection, all manner of signal/noise separation.
Both are available as code of various flavors, most common being Matlab. Both can be used as the basis for subtractive s/n reduction, or simply separation so one can use that as a decision making tool for what other analysis or alteration techniques to apply. I can help with describing what they do and how, and can assist with existing code location and code author assistance/advice, but I can't code for squat. Rather I can, but if you need anything newer than Apple ][ machine level programming or more general that SPSS automation, you'd best look elsewhere.
"No matter what you're trying to do, it's good to remember that just as weeds are plants you don't want, noise is signal you don't want." -- Karl Pribram (1919 - 2015)