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 [email protected] http://lists.linuxaudio.org/mailman/listinfo/linux-audio-dev
