Subject: Re: Spectrogram Inversion Toolbox From: Peter Meijer <feedback@xxxxxxxx> Date: Tue, 5 Aug 2014 10:02:52 +0200 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>Hi Malcolm, Thank you for releasing this toolbox which piqued my curiosity. Maybe one or two dependencies were overlooked, or an external dependency (on the Matlab Signal Processing Toolbox) not documented? I got >> TestSpectrogramCode Undefined function 'hamming' for input arguments of type 'double'. Error in ComplexSpectrogram (line 42) h = hamming(windowSize)'; Error in TestSpectrogramCode (line 25) testSignalSpectrogram = ComplexSpectrogram(testSignal, windowSize, frameStep); Thanks! Peter Meijer Seeing with Sound - The vOICe http://www.seeingwithsound.com On 04-Aug-14 10:58 PM, Malcolm Slaney wrote: > I’m happy to announce that the Spectrogram Inversion Toolbox is now available. > This is Matlab code that finds a waveform that best fits a given spectrogram. > > You might ask why this is being announced on the auditory mailing list. The > first time I needed this was when I was working on our correlogram inversion > work. It’s also a function included in the NSL (Neural Systems Laboratory) > toolbox from Univ. of Maryland. (Although this new implementation is faster and > better.) And it’s useful if you are doing anything like audio morphing. > > The source code is online now at > > http://research.microsoft.com/en-US/downloads/5ee40a69-6bf1-43df-8ef4-3fb125815856/default.aspx > > And more details are below. Enjoy. > > --- Malcolm > > The Spectrogram Inversion Toolbox allows one to create spectrograms > > from audio, and, more importantly, estimate the audio that generates > > any given spectrogram. This is useful because often one wants to > > think about, and modify sounds in the spectrogram domain. > > There are two big problems with spectrogram inversion: most importantly, > > one (generally) drops the phase when computing a spectrogram, and two > > not every (spectrogram) image corresponds to a valid waveform. This > > code finds the waveform that has a magnitude spectrogram most like the > > input spectrogram. > > The easy solution is to just do the inversion assuming some phase (like 0). > > Back in the time domain you get an answer, but there is a lot of > > destructive interference because the segments of adjacent frames do not > > have consistent phase. Some people advocate starting with a random > > phase. > > A better solution to this problem is to use an iterative algorithm > > proposed by Griffin and Lim many decades ago.It does converge, but > > slowly. > > An even better solution is to do the inversion, explicitly looking > > for a good set of phases. This toolbox does that, after the inverse > > Fourier transform of each slice, by finding the best time delay so the > > new frame and the summed frames to now are consistent. This is equivalent > > to starting with some arbitrary linear phase. The effect of this is to > > reduce the reconstruction error by an order of magnitude. Hurray. >