Re: FFT - Spectrum Analyzer

[Juan Pablo Carbajal]

On Mon, Jun 11, 2012 at 10:36 AM, Damian Harty <address@hidden> wrote:
> Why would one perform a Fourier-based analysis on something so clearly 
> non-stationary as music? I think wavelets are the tool of choice.
>
> Damian Harty
> Senior Research Fellow
> Coventry University
> +44(0)24 7688 8924
> +44(0)7799 414832
>
>
> -----Original Message-----
> From: address@hidden [mailto:address@hidden On Behalf Of Markus Bergholz
> Sent: 10 June 2012 21:50
> To: Thomas D. Dean
> Cc: address@hidden
> Subject: Re: FFT - Spectrum Analyzer
>
> On Sun, Jun 10, 2012 at 5:18 PM, Thomas D. Dean <address@hidden> wrote:
>> On 06/09/12 15:27, Renato S. Yamane wrote:
>>>
>>>
>>> Hi,
>>>
>>> Anyone knows an way to analyze, with Octave, the Spectrum Frequency of a
>>> digital media file (like an MP3)?
>>> Something like this:
>>> http://img268.imageshack.us/img268/6345/bassiloveyou.jpg
>>>
>>> Thanks and best regards,
>>> Renato S. Yamane
>>> _______________________________________________
>>> Help-octave mailing list
>>> address@hidden
>>> https://mailman.cae.wisc.edu/listinfo/help-octave
>>>
>>>
>>
>> http://labrosa.ee.columbia.edu/matlab/mp3read.html
>>
>
> i guess this is not what he want.
> he want a frequency analysis.
>
>
> %Fourier Transform of Sound File
>
> %Load File
> file = 'e-neu.wav';
> [y,Fs,bits] = wavread(file);
>
> Nsamps = length(y);
> t = (1/Fs)*(1:Nsamps);          %Prepare time data for plot
>
> %Do Fourier Transform
> y_fft = abs(fft(y));            %Retain Magnitude
> y_fft = y_fft(1:Nsamps/2);      %Discard Half of Points
> f = Fs*(0:Nsamps/2-1)/Nsamps;   %Prepare freq data for plot
>
> %Plot Sound File in Time Domain
> figure
> plot(t, y);
> xlabel('Time (s)')
> ylabel('Amplitude')
> title('fft action')
>
> %Plot Sound File in Frequency Domain
> figure
> plot(f, y_fft);
> xlim([0 1000])
> xlabel('Frequency (Hz)')
> ylabel('Amplitude')
> title('Frequency Response of Tuning Fork A4')
>
>
> but this is not my own code. i've grabbed it somewhere while building
> an arduino guitar tuner and played with this code.
>
>
>
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If wavelets is too a big word for you, you can try the function
specgram in Octave. It basically does FFT on time windows (incipient
wavelet).



-- 
M. Sc. Juan Pablo Carbajal
-----
PhD Student
University of Zürich
http://ailab.ifi.uzh.ch/carbajal/