I'm working with audio data analysis through FFT algorithm. My example audio is a sine wave at 440 Hz and 44100 Hz sampling rate.
FFT methods in programming, like
scipy.fft(y), require a vector of samples and a number of points/samples to analyze.
Sample rate is used to determine the width of each frequency range/bin in the resulting data vector (FS/N).
I've read that to increase frequency resolution of FFT results one should dicrease sampling rate and increase window size (number of samples).
I understand that I can change the N value (samples count) that I pass to the algorithm.
But if the audio is at 44100 Hz how can I dicrease it?
Would the resulting frequency bands reflect incorrect information about magnitudes of the FFT data?
Or should I change the input audio data somehow (manipulating directly the samples in the vector) before FFT so the data is passed with lower rate (say at 22050 Hz)?