On Mon, May 5, 2014 at 12:25 PM, Ricky Huang <[email protected]> wrote:
> On May 2, 2014, at 6:27 PM, J Decker <[email protected]> wrote: > > wouldn't have to be a custom filter, just decompress the media file the > normal way..... could actually probably just use the ffmpeg command line > tool to strip the audio and save it as raw samples, then just read the > audio file directly… > > > Thank you for the reply. Can you clarify it a bit for me: does saving the > audio as raw samples using ffmpeg perform the FFT necessary to convert > audio to frequency-along-time output? > > No; I guess there is some sort of filter available for that; but I thought that was what you wanted to do ... that is apply your FFT algorithm to data, and just needed the data. > Thank again. > > > > > On Fri, May 2, 2014 at 5:48 PM, Ricky Huang <[email protected]> wrote: > >> Hello all, >> >> I am trying to reproduce the Shazam algorithm as outlined in Avery Wang's >> paper "An Industrial-Strength Audio Search Algorithm" ( >> http://www.ee.columbia.edu/~dpwe/papers/Wang03-shazam.pdf). One of the >> step in this is to convert the audio to spectrogram and identify the >> spectrogram peaks. I am wondering if building a custom audio-filter for >> ffmpeg would be the correct way to go? If so, does anyone have any >> pointers on converting the audio data to spectrogram for me? (algorithm to >> use, things to note, etc?) >> >> >> Any help would be appreciated. Thanks. >> >> >> >> >> _______________________________________________ >> Libav-user mailing list >> [email protected] >> http://ffmpeg.org/mailman/listinfo/libav-user >> >> > _______________________________________________ > Libav-user mailing list > [email protected] > http://ffmpeg.org/mailman/listinfo/libav-user > > > > _______________________________________________ > Libav-user mailing list > [email protected] > http://ffmpeg.org/mailman/listinfo/libav-user > >
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