Reply by Country_Chiel December 5, 20042004-12-05
"Eric Jacobsen" <eric.jacobsen@ieee.org> wrote in message
news:41b0bb23.928505843@news.west.cox.net...
> On Sat, 04 Dec 2004 01:07:34 +0800, Steve Underwood <steveu@dis.org> > wrote: > > >John Bailey wrote: > > > >> The basics are at: > >> http://www.music-cog.ohio-state.edu/Music829D/Notes/Infotheory.html > >> > >> Thanks to the stimulation of your question, with a search based on the > >> key words: hmm, entropy, and music I have learned the question is of > >> significance today for serveral reasons: > >> 1) Recognizing when TV commercials are playing. > >> 2) Separating out background music behind speech in speech > >> recognition. > > > >I wonder if they could figure a why to identify background music and > >separate it from the sound reaching my ears :-) > > Good point! If the predictor works then you can make a pretty good > canceller! >
Not sure how you can come to that conclusion. If you have one microphone and a perfect algorithm you could determine what is music and what is speech.However, to cancel the music you would need to subtract it from the sum of music + speech and without a second sensor this would not be possible - unless you assume the statistics of the music do not change rapidly so that the music during the speech was approx the same as during non-speech - an assumption which may be true for some music maybe? On the other hand if we used multiple microphones then maybe we would have something worthwhile. Tom
Reply by Stephan M. Bernsee December 4, 20042004-12-04
On 2004-12-04 00:54:56 +0100, Richard Dobson 
<richarddobson@blueyonder.co.uk> said:

> African musicians say "every wrong note is a new style" (cited by > Christopher Small in his book "Music of the Common tongue"); but a > wrong formula is just plain wrong, leaving very little scope within > mathematics for rhetoricism.
Absolutely. If someone made a mistake, my mathmatics professor always used to say "You're almost right!" Seeing that the student looked happy, he added: "Don't look too happy - I could have said that you're totally wrong, because to a mathematician that's the same - but I wanted to be polite". :-) -- Stephan M. Bernsee http://www.dspdimension.com
Reply by Martin Eisenberg December 4, 20042004-12-04
Richard Dobson wrote:

> Music has been described as "audible mathematics" (obvious > Pythagorean notion here); but (writing as a confirmed non- > mathematician) I wonder how keen mathematicians really are > on surprises, contradictions, non-sequiturs, etc! African > musicians say "every wrong note is a new style" (cited by > Christopher Small in his book "Music of the Common tongue"); > but a wrong formula is just plain wrong, leaving very little > scope within mathematics for rhetoricism.
While that last remark is certainly true, the actual doing of mathematics starts out with inductive reasoning and tinkering like any other trail on the quest for knowledge. I would liken the musical notion of wrongness you mention to seeming incongruence at that stage rather than to formal incorrectness. Of course, it is paramount to follow up on mathematical intuition with rigorous deduction -- if you end up with a contradiction there's a mistake somewhere, no arguing. But if you cannot manage that you might just be on to something new! So yes, surprise has much value in mathematics. The difference is that music has no absolute reference frame for truth; it is neither capable nor in need of going beyond induction. At least that's my view, as ideological as the opposite assertion. Martin -- Quidquid latine dictum sit, altum viditur.
Reply by Andor December 4, 20042004-12-04
Eric Jacobsen wrote:
> On Fri, 3 Dec 2004 15:36:04 +0100, Stephan M. Bernsee > <spam@dspdimension.com> wrote: > > >On 2004-12-03 14:19:03 +0100, Ken Prager <prager_me_@ieee.org> said: > >> <http://eigenradio.media.mit.edu/> > > > >ROTFL!!! This is *really* cool. > > Very interesting. I doubt any of it is going to make it onto my MP3 > player, but it's an intereting concept.
I just downloaded the eigenradio christmas album - I find it very relaxing! Included is a neat collection of high resolution fractal snowflakes (called eigenflakes). I think that is the CD cover :-). Regards, Andor
Reply by Andor December 4, 20042004-12-04
glen herrmannsfeldt wrote:

> I would think a pure sine wave should be low complexity, so maybe > you should compress the Fourier transform.
I think a vocoder does something similar: linear predictive coding tries to fit an AR model to the input, effectively searching for the formants (resonant peaks) of the "vocal tract" transfer function. If you initialize an IIR filter with the LPC coefficients and the states (delays) with the signal, you can let it "ring" like an oscillator - the output will converge to a sum of pure damped sine waves at the estimated frequencies of the formants. However, instead of storing the sine waves, the vocoder stores the LPC coefficients and the residue (prediction error). To take this back to entropy, the energy of the prediction error could well be regarded as the entropy of a vocal signal - it gives a good measure on how unexpected the signal is, given its past history. Recent work has shown that this method is also suited for general audio signals, not just speech. The order of the AR model just increases drastically (for interpolation, orders of 1000 - 3000 are used). The same applies here for the prediction error and the entropy.
> Has anyone ever done an FFT of a whole CD?
If you take a music CD, I would expect a linear trend of the form 1/f^a. This is a common model for music signals, and it agrees well with findings of long-range correlated time series. For speech, I would guess a rectangular pulse response. The formants vary across a certain frequency range, but are limited from above and below.
> > -- glen
Regards, Andor
Reply by oookhc December 4, 20042004-12-04
"lucy" <losemind@yahoo.com> wrote in message news:<coo4it$2s2$1@news.Stanford.EDU>...
> I have vaguely heard about this method... and I am very interested in it... > could anybody give me some pointers? > > After learning how to measure entropy of music... I can begin to measure > entropy of texts, etc.. that's going to be fun!
Well, theoretically speaking, you should just treat the "notes" of the music as "symbols" for the computation of the entropy. Then, there is no difference between finding the entropy of text and finding the entropy of music. But if you sample the signal of music, encode it, and compute the entropy, I doubt if it makes sense to do that given the fact that you already have the "notes" of the music. If you just want to know what is about "entropy of data", you might just start with any textbook for "Information theory" or some websites for some ideas, e.g., http://www.ScienceOxygen.com/signal.html http://www.ScienceOxygen.com/electrical.html Have fun,
Reply by John Bailey December 3, 20042004-12-03
On Fri, 03 Dec 2004 17:49:47 +0000, Timothy Murphy
<tim@birdsnest.maths.tcd.ie> wrote:

>As a matter of interest, >do you consider high entropy good or bad? >
On 3 Dec 2004 14:42:51 -0800, gowan4@hotmail.com (gowan) wrote:
> >The important 20th century composer Paul Hindemith once wrote that he >found music to be interesting to listen to when he had a low success >rate at predicting what would happen next. I think he was thinking of >higher level structures than single notes, but couldn't the concept of >entropy apply to these higher structures as well?
>Presumably a completely random series of notes would have very high entropy, >while absolute silence has very low entropy. >I wouldn't have thought either was very enjoyable.
Both of your comments are quite stimulating. Of course! The idea that good music is neither too rote nor too random is not new but the idea that entropy as a concept allows a deeper investigation of what people like is exciting. Conjecture: classes of composers cluster around various levels of entropy. On further thought--what is predictable changes with audience familiarity with a style. Music that is on the leading edge of predictability is the most interesting. Its probably all about what gives our music neurons a good workout. John Bailey http://home.rochester.rr.com/jbxroads/mailto.html
Reply by Andrew Reilly December 3, 20042004-12-03
On Fri, 03 Dec 2004 16:38:23 +0000, John Bailey wrote:
> For written language, the analog is how many bits are needed to > confirm an informed guess as to the next letter in a text. Perhaps no > more than three. For some TV shows these days, its only two. > > For music, the question gets really challenging as one considers the > entropy of scores--the parts played by accompanying instruments and > the choices of these instruments requires a lot of encoding. In this > case, the number of bits needed to feed a high level orchestral > synthesizer might establish a lower bound.
Very much a lower bound, I suspect, because even a fantastic orchestral synthesizer would be to an orchestra as a typesetter would be to the handwritten word: you don't only have the notes, you have the playing of each of them, and the interplay of the playing with the acoustics of the hall, etc. Still, it's a neat thought experiment. And you could indeed do an interesting analysis of musical scores, rather than muscial recordings. -- Andrew
Reply by Richard Dobson December 3, 20042004-12-03
gowan wrote:

...
> The important 20th century composer Paul Hindemith once wrote that he > found music to be interesting to listen to when he had a low success > rate at predicting what would happen next. I think he was thinking of > higher level structures than single notes, but couldn't the concept of > entropy apply to these higher structures as well?
It can apply at all levels; even within one note in the hands of a master player/singer. The real interest here is the "middle ground" (to borrow a term from Schekerian analysis); where a predictable context is established (which in turn demands a knowing listener: a cognoscento), in order for a subsequent unpredictable event to have a desired rhetorical effect. One of the reasons "total serialism" ultimately failed over time as an idiom was that it was easy to demonstrate that its outputs were cognitively indistinguishable from randomly generated music. So total entropy is bad, and total un-predictability is bad also. Composers such as Trevor Wishart (waving the flag for UK composers here!), working in the medium of electro-acoustic music (aka "tape music",) go to considerable lengths to establish a viable cognitive framework (there is typically no score or equivalent text to follow, from which to learn structure), e.g. by using straight repetition to establish "this is a theme[= signficant source material to be noted by the listener]"; where that theme is some abstract sound. The idiomatic gestures of this music are unfamiliar to those brought up on maintstream Western Art Music - it takes some time to get used to the idea of timbre being a primary determinant of musical structure. Schoenberg started it with his idea of "klangfarbenmelodie" (melody of tone colours), Varese ran with it ("organised Sound"), and current electro-acoustic composers have gone super-luminary with it. Music has been described as "audible mathematics" (obvious Pythagorean notion here); but (writing as a confirmed non-mathematician) I wonder how keen mathematicians really are on surprises, contradictions, non-sequiturs, etc! African musicians say "every wrong note is a new style" (cited by Christopher Small in his book "Music of the Common tongue"); but a wrong formula is just plain wrong, leaving very little scope within mathematics for rhetoricism. I suspect much of the deep background of the debates and spats seen on this list reflects a profound need to be rhetorical, expressive and, dare I say it, emotional! Music, in contrast, is not a simple binary right/wrong medium: hence (when we have that middle ground) it is something one can not only learn, but also learn from. "Discuss..." :-) Richard Dobson Richard Dobson
Reply by gowan December 3, 20042004-12-03
john_bailey@rochester.rr.com (John Bailey) wrote in message news:<41b07a0d.180894873@news-server.rochester.rr.com>...

<snip>

> > The model of entropy that can be readily recognized: > In music--how often can an informed listener infer the next note in a > phrase; ie how many bits are needed to specifiy the next note. > In sound--how many bits are needed to specify the next value of the > signal. >
<snip> The important 20th century composer Paul Hindemith once wrote that he found music to be interesting to listen to when he had a low success rate at predicting what would happen next. I think he was thinking of higher level structures than single notes, but couldn't the concept of entropy apply to these higher structures as well?