Luis Garrido-4 wrote:
>
> The biggest problem is defining what is 'similar' . Then how 'similar'
> you want to get.
>
> If you want to find an exact replica of the model sample within the
> larger audio file a cross-correlation analysis is very simple and
> might yield good enough results.
>
> If you want a system with a better generalization ability, perhaps you
> can extract certain parameters of the signal and feed them to some
> classifying system. You could for instance use a set of model samples
> to train a neural network and see how it reacts to the whole file.
>
> There are libraries that could help you with both approaches.
>
> But you need a good definition of the problem you want to solve and
> bear in mind that what seems simple for your human brain might be
> extremely complex to replicate artificially. It depends on what kind
> of results are you demanding of your system. You need also a solid
> background in digital signal processing. There is some general
> literature on the subject available on the net.
>
> There is a lot of literature on automated signal classification since
> it is a rather useful feature to have (voice recognition is a prime
> example): books, IEEE papers...
>
I do not want to find an exact replica of the model sample. I am definitely
more interested in the second approach you describe - extract certain
parameters of the model signal and then find something with similar values
for those parameters in the second.
I am hoping to find a library that might abstract away some of the low level
theory for me. What libraries did you have in mind?
-- View this message in context: http://www.nabble.com/Detecting-one-sample-within-another-tf4744254.html#a13567550 Sent from the linux-audio-dev mailing list archive at Nabble.com. _______________________________________________ Linux-audio-dev mailing list Linux-audio-dev@email-addr-hidden http://lists.linuxaudio.org/mailman/listinfo/linux-audio-devReceived on Sun Nov 4 04:15:02 2007
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