Gale Andrews wrote:Clip Fix can also be used almost like a waveshaper to construct peaks in audio that isn't clipped but perhaps overcompressed. I quite often use it like that - illegitimate or not I think it does a great job in those cases to breath life back into the audio (and much easier to use than a conventional expander).
Interesting. I've never tried that. I'd guess that it would be most "natural" on audio that had been heavily "limited" - something which is very difficult to combat by other means. I'll have to try it
Gale Andrews wrote:To me, asking for Clip Fix to use the Repair algorithm is still tantamount to asking for Repair to work automatically on longer selections (otherwise, why not carry on painstakingly using Repair as now)?
I think there is a distinction between the proposals.
I don't recall seeing this in Audacity, but according to the code:
Code: Select all
This was formerly the PopClickRemoval effect, but it was
renamed and focused on the smaller subproblem of repairing
the audio, rather than actually finding the clicks.
So originally it looks like it was intended to be a two pass effect - first detect damaged audio, then fix it. That approach is like ClipFix, but ClipFix uses a repair algorithm that does not require as much "good" audio between the "bad" parts.
Asking Repair to work automatically on longer sections than now is easy to program. The problem is that it becomes increasingly slow. With only a modest increase in size it could take several minutes to process each selection. With the amount of increase that most users want you could be waiting for hours.
Quant wrote:As far as I can see, Repair only fails dismally when a damaged area is surrounded by other damaged areas that occur periodically with a frequency similar to the fundamental frequency of the underlying signal. In all of the cases where I have used Repair on an interesting signal, like music ripped from a CD or my own recordings, this rarely happens.
I doubt that is true, though it may appear to be the case.
Looking casually at your "Clipping Example" there appears to be one bad section every 210 samples or so, but that is because you are intelligently grouping together multiple regions of bad samples that have a few good samples mixed in. It is very easy to "see" the groupings, but much harder and slower to write an algorithm that can make the grouping sufficiently intelligently to fit the general case (rather than just one or two specific cases).

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