Hello Nick Wray, Let me offer a simplified explanation of what's going on. Sorry if it's unnecessary.
Sound is waves of pressure in the air. Devices like microphones can measure the changing pressure by converting it into voltage. Voltage can then be sampled by an analog-to-digital converter inside a sound card and stored as numbers in computer memory. On Fri, 1 Feb 2019 10:20:57 +0000 (GMT) Nick Wray via R-help <r-help@r-project.org> wrote: > What I am not sure about, and I can't find any clear explanation, is > what these elements actually stand for? Digital sound works by measuring "pressure" a few tens of thousands of times per second and then recreating the corresponding signal elsewhere. According to the sampling theorem, sound sampled N times per second would be losslessly reproduced if it didn't contain frequencies above N/2 Hz. To reiterate, these numbers are just audio samples. Feed them to the sound card at the original sample rate, and you hear the same sound that had been recorded. This part is explained well in two 30-minute video lectures here: https://xiph.org/video/vid1.shtml https://xiph.org/video/vid2.shtml (I wouldn't normally recommend video lectures, but these are really good.) > I would have thought that one needed as a minimum both volume and > frequency ie a two dimensional vector but as far as I can tell there > is only one single vector. You are describing a spectrogram: a surface showing the "volume" of each individual frequency in the sound recording, over time. How to get it? If you run a Fourier transform over the original vector, you will get only one vector showing the magnitudes and phases of all frequencies through the whole length of the clip. To get a two-dimensional spectrogram, you should take overlapping parts of the original vector of samples, multiply them by a special window function, then take a Fourier transform over that and combine resulting vectors into a matrix. Computing a spectrogram involves choosing a lot of parameters: size of the overlapping window, step between overlapping windows, the window function itself and its own parameters. Problems like these should be described in books about digital signal processing. Jeff Newmiller sent more useful links while I was typing this, and I guess I should posting off-topic. -- Best regards, Ivan ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
