[mirtoolbox] Re: MIR classify
- From: Ersin Karcı <ersin.kar@xxxxxxxxx>
- To: mirtoolbox@xxxxxxxxxxxxx
- Date: Thu, 18 Nov 2010 07:51:41 +0100
Dear Martin,
So is there a way to use frame decompostioned version of mfcc coefficients
("a" in your previous email) in mirclassify function? I that will solve my
problem.
Regards
Ersin
On Tue, Nov 16, 2010 at 11:27 PM, Martín Hartmann <
martinarielhartmann@xxxxxxxxx> wrote:
> Dear Ersin,
>
> if I am correct, the default frame parameters are used for extraction
> and the result gives the averaged values for each of the 13
> coefficients. But let us get a frame decomposition with the
> 'Frame' option:
>
> a = mirmfcc ('Amaj3', 'Frame');
> mirgetdata (a)
>
> Best,
>
> Martin Hartmann
>
> On Tue, Nov 16, 2010 at 11:29 PM, Ersin Karcı <ersin.kar@xxxxxxxxx> wrote:
> > Dear Martin,
> >
> > In this example for each audio samples there are only one (13x1) mfcc
> > set, which actually I can not understand how it is meaningful. As far
> > as I know mfcc's are calculated frame by frame and frame sizes are
> > about 10-100 mseconds ( varies according to the problem). The audio
> > samples should contain
> > more than 1 frame so, more than 1 mfcc sets.
> >
> > Am I thinking wrong or am I missing some point?
> >
> > Sorry for too much questions and thanks for your help.
> >
> > Best Regards
> >
> > Ersin
> >
> >
> > On Tuesday, November 16, 2010, Martín Hartmann
> > <martinarielhartmann@xxxxxxxxx> wrote:
> >> Dear Ersin, there is no need to use mirframe unless we wish to change
> >> its default values.
> >>
> >> Maybe this working example using the sets in the MIRToolboxDemos
> >> folder can clarify this issue.
> >>
> >> Martin Hartmann
> >>
> >> cd /Applications/Matlab/toolbox/MIRtoolbox1.3.1/MIRToolboxDemos/test_set
> >> test = miraudio ('Folder', 'Label', [1 2]);
> >> cd ..
> >> cd train_set
> >> train = miraudio ('Folder', 'Label', [1 2]);
> >> mfcc_test = mirmfcc (test);
> >> mfcc_train = mirmfcc (train);
> >> mirclassify (test, mfcc_test, train, mfcc_train)
> >>
> >>
> >>
> >>
> >>
> >> On Tue, Nov 16, 2010 at 12:50 AM, Ersin Karcı <ersin.kar@xxxxxxxxx>
> wrote:
> >>> Dear Martin,
> >>> Thank your for your reply.
> >>> Unfortunatelly I couldn't get the exact solution to my problem, let me
> >>> explain myself again.
> >>> For example, I have an audio sample of 10 seconds.
> >>>
> >>> If I use the the miraudio and mirmfcc functions in order, I obtain a
> 13x1
> >>> mfcc vector. I guess this vector is obtained by using all the audio
> sample.
> >>> But as far as I know mfcc is calculated for every each frame of the
> audio
> >>> sample. ( Lets say the frame size is 50mseconds) In this case I obtain
> a
> >>> 13x20 mfcc vector. And by using this in mirclassify I get the error in
> my
> >>> previous email.
> >>> At this step I couldn't get where I am mistaken. Does using mirframe
> before
> >>> calculating be helpful and also useful for my problem or do you prefer
> any
> >>> other solution?
> >>> Thank you and sorry for not understanding qucikly.
> >>> Regards
> >>> Ersin
> >>>
> >>> On Mon, Nov 15, 2010 at 7:35 PM, Martín Hartmann
> >>> <martinarielhartmann@xxxxxxxxx> wrote:
> >>>>
> >>>> Dear Ersin,
> >>>>
> >>>> You can extract multiple analytic features from the train and test
> >>>> sets at the same time with mirclassify. Simply create an object for
> >>>> each feature (e.g., spectral centroid) or feature set (e.g., MFCCs)
> >>>> you wish to use. For example: mirclassify(test, {mfcc(test),
> >>>> centroid(test)}, train, {mfcc(train), centroid(train)})
> >>>>
> >>>> I strongly recommend you to read the page 163 of the MIRtoolbox Users'
> >>>>
> >>>> Guide:
> https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/mirtoolbox/MIRtoolbox%20Users%20Guide%201.3
> >>>>
> >>>> Best,
> >>>>
> >>>> Martin Hartmann
> >>>>
> >>>> On Sun, Nov 14, 2010 at 11:49 PM, Ersin Karcı <ersin.kar@xxxxxxxxx>
> wrote:
> >>>> >
> >>>> > Dear All,
> >>>> > I am trying to use mirclassify, with my additional features. As far
> as I
> >>>> > understood the there are only one set of features per one audio
> sample used
> >>>> > as an input (mirclassify(test,mfcctest,train,mfcctrain) where mfcc
> test is
> >>>> > 13x1 feature vector).
> >>>> > In my problem I am calculating those features per frames. If we
> assume
> >>>> > that the audio sample is 10 seconds length, with 50msec frames I
> obtain
> >>>> > 13x20 mfcc coefficients per audio sample. While using this as the
> input I
> >>>> > obtain the following error:
> >>>> > ??? Subscripted assignment dimension mismatch.
> >>>> > Error in ==> mirclassify.mirclassify>integrate at 176
> >>>> > vtl(:,l) = vl;
> >>>> > Error in ==> mirclassify.mirclassify at 39
> >>>> > vt = integrate(vt,get(dt{i},'Data'),lvt,norml);
> >>>> >
> >>>> > The same issue is the same for other features.
> >>>> > Can you help me with this issue?
> >>>> > Regards
> >>>> > Ersin KARCI
> >>>>
> >>>>
> >>>> --
> >>>> Martin Ariel Hartmann
> >>>> Lic. in Psychology | Music, Mind and Technology MA Candidate
> >>>> +358 (0) 4 6581 2384 | martinarielhartmann@xxxxxxxxx
> >>>>
> >>>
> >>>
> >>
> >>
> >>
> >> --
> >> Martin Ariel Hartmann
> >> Lic. in Psychology | Music, Mind and Technology MA Candidate
> >> +358 (0) 4 6581 2384 | martinarielhartmann@xxxxxxxxx
> >>
> >>
> >
> >
>
>
>
> --
> Martin Ariel Hartmann
> Lic. in Psychology | Music, Mind and Technology MA Candidate
> +358 (0) 4 6581 2384 | martinarielhartmann@xxxxxxxxx
>
>
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