Representation for music
Author
Does anyone have any references or ideas for representations of music for pattern recognition?
-Kirk
Music? You mean like manuscript type or analog sounds? I would probably use <note frequency, duration, volume profile over the duration, instrument, k-discrete sequence index>
Hehe, sounds like a fun project brewing in your mind.
Hehe, sounds like a fun project brewing in your mind.
I was at a conference in 2003 where someone was showing off a GA that could generate the instrumental part of a composition when given a melofy. It was a pretty cool concept.
Author
Not manuscript, but rather analog. Also, rather than just sounds, I'd be interested in a representation for a whole song or performance. Most of the features you (Nick) mentioned appear to be associated with a single note as opposed to a (short) composition of notes.
Interesting GA application, too. That's something I'd like to see.
As for what's brewing in my mind, I have too many ideas. 8^) Make the voices stop!!
-Kirk
Interesting GA application, too. That's something I'd like to see.
As for what's brewing in my mind, I have too many ideas. 8^) Make the voices stop!!
-Kirk
hehe.. the voices are crazy, especially the one of the rabbit with long ears that plays the violi... oh wait you don't get that one too?
What I meant was to group those notes in sequence and you could have several instruments playing at once. What? You can't read minds?
Anyway, I'm not sure what you are driving at on the analog... but you could extract those features from an analog signal I suppose by using an FFT or Wavelet transform... (I venture to guess here...)
What I meant was to group those notes in sequence and you could have several instruments playing at once. What? You can't read minds?
Anyway, I'm not sure what you are driving at on the analog... but you could extract those features from an analog signal I suppose by using an FFT or Wavelet transform... (I venture to guess here...)
Wouldn't MIDI be a good way to represent the music? MIDI events are easily analysed and processed, and also come quite close to being able to reproduce the original, at least on harmonic, rhythmic, and melodic levels.
I've come across the use of RBF networks (radial basis function networks) recently for classification of music, so you might get some ideas from reading that literature. Should be easy to find online (that's where I saw it, but don't remember the authors off-hand).
As for representation of sounds, you might consider computing the complex cepstrum and performing classification in the space of coefficients of this transform.
Cheers,
Timkin
As for representation of sounds, you might consider computing the complex cepstrum and performing classification in the space of coefficients of this transform.
Cheers,
Timkin
Author
Timkin,
Thanks for the references to RBFs and the ideas for representations. I have a feeling I'm going to have to do a lot of reading. 8^) Is it any wonder we love this stuff??
-Kirk
Thanks for the references to RBFs and the ideas for representations. I have a feeling I'm going to have to do a lot of reading. 8^) Is it any wonder we love this stuff??
-Kirk
whoa big words! *falls over*
While I bookmark the searches for later reading, I'd suggest Midi too. I've seen analyzers that get input from a microphone and store the result on a Midi. You could do that, and then check for patterns in midi.
Of course, you'd lose details like vibrato and such. Which makes it simpler to look for patterns.
While I bookmark the searches for later reading, I'd suggest Midi too. I've seen analyzers that get input from a microphone and store the result on a Midi. You could do that, and then check for patterns in midi.
Of course, you'd lose details like vibrato and such. Which makes it simpler to look for patterns.
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