Hello, i'm sorry if i'm not posting in the right Category, i'm new to the forum.
I'm working on a project for hiking help for android, and i thought about a functionnality that can be fun, recognizing a bird's singing. The idea is to record a bird that you pass by and the database tells you which species it is.
I'm not a pro of sound processing, but i though that implementing an FFT could help. I was planing on using the FFT to get the max-min amplitude and compare it with the database's pre-processed information, of course i don't plan on using only the min-max indicators.
I inspired my code from this: https://github.com/blanche/shayam/blob/master/java/at.lw.shayam/src/at/lw/shayam/AudioAnalysis.java and as much as i undestand the maths behind the fourrier transform, i don't get everything in that code.
So here are my questions:
The chunks are used to accelerate the computing time of the FFT ? if we have a 2^n chunks, we'll have 2^n smaller FT processed ?
The results[][] 2d Complex Array contains... complexs. But i don't understant what is x and y in results[x][y], how can you find the frequency and the amplitude. (of course i'll have to convert the complexs to doubles)
Do you think this approach is enough ? the projet is not professional so i'm not trying to get a recogntion rate of 100% !
Thank you for your answers.