Comment by barrkel
10 years ago
You can also view digital images as 1-dimensional arrays of bits. (This is roughly how fax machines work.) That doesn't mean they can't also be 2-dimensional images, or representations of 3-dimensional images, or indeed an encoding of a 3D scene directly.
Similarly, you can unpack a linear sequence of sound samples into a two-dimensional plot of frequency and amplitude with a fourier transform.
Or you can represent the music as instructions to performers or synthesizers (ie notation) and you've got as many dimensions as you want.
Music is not sound, it's made of sounds. The fact that it gets mixed down to a single waveform when you consume it, either in the studio or when it hits your ear, isnt particularly relevant to how its made. I suppose the same is true of images though.
Markov chains applied to midi have been able to make "locally similar" stuff since forever. I wonder how this algorithm could be applied to higher-order aspects of music notation.
> Or you can represent the music as instructions to performers or synthesizers (ie notation) and you've got as many dimensions as you want.
These are just multiple signals in a single dimension (time).
1 physical dimension. Mathematically, each signal is a dimension.
1 reply →
> Similarly, you can unpack a linear sequence of sound samples into a two-dimensional plot of frequency and amplitude with a fourier transform.
Fourier transform by itself is still 1D (amplitude vs. frequency); to get to 2 dimensions you can plot it over time i.e. a spectrogram.