I'm doing a project on audio classification, mainly focused on Bird sounds.
I would like to know which is the best similarity measure that I can adopt to check test signal with training data.
I intent to do the project in matlab.
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Sign up to join this communityI'm doing a project on audio classification, mainly focused on Bird sounds.
I would like to know which is the best similarity measure that I can adopt to check test signal with training data.
I intent to do the project in matlab.
I would like to know which is the best similarity measure that I can adopt to check test signal with training data.
Welcome to engineering. There is no universally "best" approach, as it always depends on your specific models.
Mathematically, as soon as you can define what "similarity" should mean, you might be able to derive something.
Assuming that bird's auditory senses kind of work similar to human hearing, I'd try with the usual audio comparison models, probably a basic MFCC thing.
As a comment: A former advisor of me once said:
A week in the lab can easily save you up to two hours of reading literature.
Really, there's a whole lot of papers, textbook introductions and wikipedia articles on sound comparison. Start with anything, and read forward. That's going to be faster than asking for a single answer to your acute problem without getting the bigger picture of how things work.
As @Marcus Müller wrote, the best similarity remains an open question depending on the context. For birds which imitate human speech, you can have a look at: The transformation of birds sounds into "speech". Other references are: A procedure for an automated measurement of song similarity or Parametric Representations of Bird Sounds for Automatic Species Recognition. A look at IEEE Xplore (as suggested by @Marcus Müller), Scopus, or Google Scholar with queries like [similarity AND ("bird sounds" OR "bird songs")] can provide results.
Even better, ask your favorite university librarian, she/he knows where to look at.