Re: [LAD] LV2 note2midi plugin

Am 10.05.2014 18:39, schrieb Florian Paul Schmidt:
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> On 10.05.2014 00:18, Lucas Takejame wrote:
>> Hello guys, recently I assembled note2midi LV2 plugin based on the
>> ‘aubionotes’ from lib aubio's example folder. You can find it at
>> this link
>> https://github.com/portalmod/mod-utilities/tree/master/Note2Midi
>> and I'm hopping you guys could help me to improve this plugin so it
>> can be more reliable for using with guitar and bass. The majority
>> of the tests were made using pure sine waves. I barely know how the
>> algorithms ‘onset’ and ‘pitch’ detection works, that’s because I
>> don't know much more how the note2midi can be improved. I
>> appreciate if someone could give me some tips =)!
>>
>> Att,
>>
>> Lucas
>>
>>
> I would be interested in trying a different approach to this problem.
> Namely using machine learning. Would the guitar players on this list
> be willing to provide training data? I.e. audio files of you playing
> single notes with an additional text file describing the played
> pitches. A format like
>
> frame-number start 440
> frame-number end
>
> e.g. you have an audio clip at 1000hz sampling rate where an 440hz A
> starts on frame 500 (at 0.5 secs) that lasts to frame 2500 (so, 2 secs
> duration):
>
> 500 start 440
> 2500 end
>
> And so on.. Also for a usable guitar synthesizer one would maybe have
> to go a step further. The closer one is to the onset of the note the
> more uncertain the pitch is (loosely and much simplified speaking: for
> a low note it takes quite a while until even half a cycle has passed -
> during that time the pitch is very uncertain), so one approach would
> be to use a percussive sound for the start of the note (onset
> detection is easier than pitch detection I would figure)

I come to opposite results, on/offset detection for a guitar becomes
real hard,
and often enough the results are simply wrong.
Which detect algo do you have in mind?

> and then once
> the pitch is established fade to a second synthesis model that
> produces a clearly defined pitch.
>
> Mapping this to a midi stream introduces some loss of information, but
> could also be possible (e.g. two midi outs, one for the percussive
> onset detection and one for the (slower) pitch detection).
>
> I wanted to try this for a long time.. Maybe using decent machine
> learning and lots of training data one could even identify the pitch
> based on the characteristics of the very early signal from a note, but
> I'm not really certain about that.
>
> Sorry for hijacking your post and talking about several separate
> things at once, but maybe someone is interested in a project like this..
>
> Flo

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Received on Sun May 11 12:15:01 2014