[PD] detect if adc~ is music or speech

[Pedro Lopes]

Sometimes data beats algoriths, but really depend on the scope.

I read this in SIGGRAPH a couple of years ago: (was regarding image matching
and blending)

"there's no good algorithm to do this, only millions of data in the
database".

:)
p.s.:There's a state of the art research project in Portugal, with speech
recognition and realtime translation of  streaming  TV, and what they use
is: massive recording data from the European parliament reunions. Massive
data.


On Tue, Feb 8, 2011 at 4:22 AM, Tedb0t <lists at liminastudio.com> wrote:

> Yeah.  Trying to define music is essentially pointless.  Defining speech
> would be easier.
>
> However, since you mentioned neural nets, you could try to train a net on
> speech and music (there's an ANN object out there that I've tested) and see
> what happens.  That would be a fun experiment, no idea how well it would
> work...  you'd need a pretty huge training set for it to be even remotely (I
> would think).
>
> ——t3db0t
>
>
> On Feb 7, 2011, at 1:38 PM, Pedro Lopes wrote:
>
> First of all, I would take it from another angle:
>
> <this is one possible way, out of zillions>
> if it is speech or not. Thus if the speech recognizer has X % of
> recogniztion rate, you inherit that percentage. Now you heavily depend on
> the recognizer, some recognizers like teh default windows try to always
> match the input to some string, thus they are a bit of garbage in academic
> terms, what you need is a strong open recognizer that can tell you how %
> similar the sentence is to a target sentence in database.
>
> Why do I suggest this angle?
> - Cause' I don't wanna think "what is music". Speech is a language, it is
> defined, it easy structured. Music? Noise is music, drone is music, ambient
> can be non rhythmical, what about an a Capella singing? Will it be music?
> and all those inherited philosophical issues. Furthermore, if you need more
> help maybe explaining the context will aid us, because if you only care for
> certain "music" can be easier. ALSO: if you have access the audio data, you
> can always extract (filter) the music.
>
> </this is one possible way, out of zillions>
>
> best,
> pedro
>
>
> On Mon, Feb 7, 2011 at 5:43 PM, patrick <puredata at 11h11.com> wrote:
>
>> would it be possible to detect if the incoming audio is music or speech? i
>> guess it's very hard, but i was thinking about some methods:
>>
>> using some kind of frequency detection
>> using bonk (if the tempo is stable = music)
>> env~ (most music are compressed nowadays)
>> training a voice (using neural network?!?)
>>
>>
>> From the author of aubio:
>> Use a few low level features, such as energy of low and high frequencies
>> bands, spectral spread. In a second step, these approaches are often refined
>> using machine learning techniques bayesian networks or support vector
>> machines.
>>
>> See for instance these papers:
>> http://cobweb.ecn.purdue.edu/~malcolm/interval/1996-085/
>> http://www.aclweb.org/anthology/O/O08/O08-1015.pdf
>> http://www.hindawi.com/journals/asp/2009/628570.html
>>
>> i would like to achieve > 90% of accuracy if possible. any suggestions are
>> welcome!
>>
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>
>
>
> --
> Pedro Lopes (MSc)
> contact: pedro.lopes at ist.utl.pt
> website: http://web.ist.utl.pt/Pedro.Lopes /
> http://pedrolopesresearch.wordpress.com/ |
> http://twitter.com/plopesresearch
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-- 
Pedro Lopes (MSc)
contact: pedro.lopes at ist.utl.pt
website: http://web.ist.utl.pt/Pedro.Lopes /
http://pedrolopesresearch.wordpress.com/ | http://twitter.com/plopesresearch
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