[DT] types of "averagers" - was [Re: counterphase detection in stereoaudio]
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From: Richard Owlett on 5 Feb 2010 14:10 *DT* defined - DIVERGING from 'topic' Jerry Avins wrote: > kork wrote: >>> Tim Wescott wrote: >>>> On Thu, 04 Feb 2010 09:57:49 -0600, kork wrote: >>>> >>>> >>>>>> kork wrote: >>>>>>> Hi folks, >>>>>>> >>>>>>> I'm going to develop a quality control application that inspects >>>>> recently >>>>>>> imported audio files for a number of checks. One of them is the >>>>> detection >>>>>>> of counterphase fragments in the file. With counterphase I mean a >> 180 >>>>>>> degrees (or pi rad, if you prefer) >>>>> phase >>>>>>> shift between the two audio channels in the (stereo) file. In a >> radio >>>>>>> broadcast of the file this is killing when it is listened through a >>>>>>> mono-receiver. >>>>>>> >>>>>>> I was thinking of subtracting one channel from the other (or reverse >> a >>>>>>> channel and add it to the other). Then flagging the audio fragments >> as >>>>>>> counterphase when the resulting signal differs a lot from zero >> during >>>>> a >>>>>>> certain amount of time. >>>>>>> But since it is likely that the 2 channels are anything but equal, >> I >>>>> may >>>>>>> never get to see a flatlioe. >>>>>>> >>>>>>> I thought maybe you DSP guys can give me some insights on this? >> Maybe >>>>>>> there's a test in the frequency domain I can think of? >>>>>> Compute (L+R) and (L-R), rectify, accumulate, compare. It is very >>>>>> obvious if the stereo channels are in phase or out of phase. >>>>>> >>>>>> >>>>>> Vladimir Vassilevsky >>>>>> DSP and Mixed Signal Design Consultant http://www.abvolt.com >>>>> Hi Vladimir, >>>>> >>>>> Thanks for your answer. >>>>> Would you mind elaborating a bit on the "rectify" and "accumulate" >>>>> suggestions? They're not so obvious terms for me in this domain. >> Thanks >>>>> again. >>>> "Rectify": take the absolute value. >>>> >>>> "Accumulate": sum up a bunch of samples. >>>> >>>> Then compare the relative strengths of the L+R and L-R channels -- >>>> normally L-R should be significantly smaller than L+R. In fact, this >> is >>>> why the 'wrong' way is a broadcast-killer -- the FM stereo broadcast >>>> protocol depends on this property, won't work without it, etc. >>>> >>>> I'll charge you money for answers, too, but only if the question takes >> >>>> more than a few lines to answer. >>> The accumulation should be lossy; i.e., include a "forgetting >>> factor". alternatively, you could dump the result after a suitable >>> time and start >> >>> over. >>> >>> Jerry >>> -- >> >> Thanks Tim and Jerry, >> >> I appreciate the jargon explanation. >> This sounds pretty straight-forward to implement. I'll have a go at it. >> >> Jerry, your "forgetting factor" sounds logical. I was thinking of just >> testing separate successive chunks of samples, so I won't have any >> "memory-effect". > > That will require counting and branching. Forgetting is actually > simpler. The convention is that x[n] is the input and y[n] is the > output. Set y[n+1] = (1-a)*y[n] + a*x[n+1]. For stability, 0 > a > 1. > Larger values forget faster. This is called an exponential averager. > > Jerry Why is this called an "exponential averager"? I have heard of "boxcar" and "running" averages. What is/are the difference(s)? What other averageres exist? The OP apparently says he is looking at *NON*overlapping chunks of data. Is there not there an *INTRINSIC* forgetting factor? |