[rec.audio] Restoration

gallaghe@husc8.HARVARD.EDU (Paul Gallagher) (07/14/88)

Here's a question maybe someone out there can answer:
Why isn't it possible to completely restore a recording: for example, to remove
all extraneous noise (hiss, clicks, coughs), even to make a reasonable guess
about information not in the original recording (for example, given a score
and a knowledge of the harmonics of a voice or an instrument, to recreate
something close to the sound of the original performance)?


PG

phd@speech1.cs.cmu.edu (Paul Dietz) (07/14/88)

In article <4944@husc6.harvard.edu> gallaghe@husc8.UUCP (Paul Gallagher) writes:
>Here's a question maybe someone out there can answer:
>Why isn't it possible to completely restore a recording: for example, to remove
>all extraneous noise (hiss, clicks, coughs), even to make a reasonable guess
>about information not in the original recording (for example, given a score
>and a knowledge of the harmonics of a voice or an instrument, to recreate
>something close to the sound of the original performance)?

Actually, this sort of thing is commonly done. I remember hearing a story
about some Caruso recordings that were restored by having a singer
imitate as closely as possible the original, and then using this to
generate optimal filters that were then applied to the original recordings.

I suggest you look at the literature on adaptive filtering. Widrow and
Stearns "Adaptive Signal Processing" in the Prentice-Hall Signal
Processing Series is a good place to start.

Paul H. Dietz                                        ____          ____
Dept. of Electrical and Computer Engineering        / oo \        <_<\\\
Carnegie Mellon University                        /|  \/  |\        \\ \\
--------------------------------------------     | | (  ) | |       | ||\\
"If God had meant for penguins to fly,             -->--<--        / / |\\\  /
he would have given them wings."            _________^__^_________/ / / \\\\-

stewarte@sco.COM (Stewart Evans) (07/16/88)

In article <2266@pt.cs.cmu.edu> phd@speech1.cs.cmu.edu (Paul Dietz) writes:

>Actually, this sort of thing is commonly done. I remember hearing a story
>about some Caruso recordings that were restored by having a singer
>imitate as closely as possible the original, and then using this to
>generate optimal filters that were then applied to the original recordings.

I have heard, admittedly second-hand, of another restoration project (or 
maybe the same one) which involved computer-modeling of the cone that 
Caruso sang into (which was apparently much like the horns used as 
"speakers"), and of its effects on the sound, then applying this 
transformation in reverse.  Needless to say this was a research project,
not a commercial endeavor...

Anyone know any more about this research?

-- 

"Stupidity is like hydrogen -
 it's a basic building block of the universe."
					-- Frank Zappa

max@trinity.uucp (Max Hauser) (07/16/88)

In article <2266@pt.cs.cmu.edu>, Paul Dietz wrote:

| In article <4944@husc6.harvard.edu> ... (Paul Gallagher) writes:
| >Why isn't it possible to completely restore a recording: for example, to remove
| >all extraneous noise (hiss, clicks, coughs), even to make a reasonable guess
| >about information not in the original recording (for example, given a score
| >and a knowledge of the harmonics of a voice or an instrument, to recreate
| >something close to the sound of the original performance)?
| 
| Actually, this sort of thing is commonly done. 

I'm not sure that I would concur with this.  People frequently suggest 
strategies similar to Paul Gallagher's, above; but the problem arises in
translating ideas like "knowledge of harmonics of a voice or an instrument"
into hard specifics, algorithms that act on the recorded information,
to do the job.  The obstacles are not in the broad concept but in the
nitty gritty.

| I remember hearing a story
| about some Caruso recordings that were restored by having a singer
| imitate as closely as possible the original, and then using this to
| generate optimal filters that were then applied to the original recordings.

Stockham at Utah, pioneering the use of serious DSP in digital audio,
used a blind deconvolution algorithm fifteen years ago to separate Caruso's
"original" voice from the severely (but linearly) distorting acoustics 
of the cylinder phonograph system that recorded him.  Blind deconvolution
is the process of recovering an original signal from a filtered version of
it without knowing what filter was used; it works when the filter and the
original signal have characteristic natural frequencies (or singularities)
in distinct regimes of frequency.  The particular algorithm in this case was
a form of homomorphic filtering [1], which is a practical example of a real
tool that can help implement the regrettably inexact idea of "separating 
desired from undesired" signals.  Stockham, BTW, formed a firm, now 
DRC-Soundstream I believe, and commercialized the method.  People who have
heard the deconvolved Caruso asserted to me that the corrupted original 
sounded better, to their ears (whether because of second-order defects in
the process or because Caruso was phonogenic, I won't presume to guess).

It may not have been the same case that Paul Dietz was referring to.

| I suggest you look at the literature on adaptive filtering. Widrow and
| Stearns "Adaptive Signal Processing" in the Prentice-Hall Signal
| Processing Series is a good place to start.

I agree with this.  Unfortunately, classical (Widrow-type LMS-linear)
"adaptive" filtering, while it is another very useful tool with a lot of 
applications, really addresses a different class of problems from what 
Paul Gallagher proposed.  They tend to be applications that can be cast in
the form of training a device (the adaptive filter) to give a precisely 
known output, or to eliminate an interfering signal that is mathematically
degenerate in some way (e.g., is narrowband) or is available in some 
distorted form itself.  Again, in every case you need a mathematical, not
just an intuitive, basis for attacking the problem.

Another basic tool that might have relevance here is dynamic time
warping (DTW), used routinely in applications like pattern recognition
where inputs (like speech) are subject to uncontrollable time-scale
expansions and compressions.  Unlike the classes of algorithms mentioned
so far, DTW doesn't assume rigid time alignment among the different
signals being manipulated and compared.  I just mention it.  I wish 
someone with a broad background would attack the problem that Paul 
Gallagher raised, or at least summarize in the literature the different
tools that are steps in that direction.  Perhaps it has been done --
if so, please post.  The different tools, characteristically, arise in
very different fields of inquiry, hence the need for broad background.

[1] Oppenheim and Schafer, _Digital Signal Processing_, Prentice-Hall
1975, Chapter 10, is a broad introduction to homomorphic sig. proc.

Max Hauser / max@eros.berkeley.edu / ...{!decvax}!ucbvax!eros!max

phd@speech1.cs.cmu.edu (Paul Dietz) (07/16/88)

Max Hauser writes:
>In article <2266@pt.cs.cmu.edu>, Paul Dietz wrote:
>| In article <4944@husc6.harvard.edu> ... (Paul Gallagher) writes:
>| >Why isn't it possible to completely restore a recording: for example, to remove
>| >all extraneous noise (hiss, clicks, coughs), even to make a reasonable guess
>| >about information not in the original recording (for example, given a score
>| >and a knowledge of the harmonics of a voice or an instrument, to recreate
>| >something close to the sound of the original performance)?

>| Actually, this sort of thing is commonly done. 

>I'm not sure that I would concur with this.  People frequently suggest 
>strategies similar to Paul Gallagher's, above; but the problem arises in
>translating ideas like "knowledge of harmonics of a voice or an instrument"
>into hard specifics, algorithms that act on the recorded information,
>to do the job.  The obstacles are not in the broad concept but in the
>nitty gritty.
> Unfortunately, classical (Widrow-type LMS-linear)
>"adaptive" filtering, while it is another very useful tool with a lot of 
>applications, really addresses a different class of problems from what 
>Paul Gallagher proposed.

I guess I jumped a head a bit on this on. I was thinking more in terms
of devices like noise cancelation systems used in cockpits where
LMS and RLS type approaches work quite well. However, I could imagine
applying very similar ideas to exactly what Paul Gallagher suggested.
For instance, let's say you had a noisey recording of a single
trumpet that you wanted to clean up. One approach might be to create
a transmission line-like filter (with harmonically related pass areas)
that could be adaptively tuned (both in frequency, and peak/valley
ratio) to obtain maximal response. Seems to me that this could work
pretty well. Of course, trying to do this for more than one
instrument at a time instantly becomes a nightmare... (Essentially,
this is equivalent to the "narrow band" problem you mentioned LMS
was good for...)

>Another basic tool that might have relevance here is dynamic time
>warping (DTW), used routinely in applications like pattern recognition
>where inputs (like speech) are subject to uncontrollable time-scale
>expansions and compressions.  Unlike the classes of algorithms mentioned
>so far, DTW doesn't assume rigid time alignment among the different
>signals being manipulated and compared. 

Sounds interesting! Do you have any references? (Probably one of
those books on multirate DSP that I always ignore...)

Paul H. Dietz                                        ____          ____
Dept. of Electrical and Computer Engineering        / oo \        <_<\\\
Carnegie Mellon University                        /|  \/  |\        \\ \\
--------------------------------------------     | | (  ) | |       | ||\\
"If God had meant for penguins to fly,             -->--<--        / / |\\\  /
he would have given them wings."            _________^__^_________/ / / \\\\-

thearlin@vdsvax.steinmetz.ge.com (Thearling) (07/19/88)

>In article (Paul Gallagher) writes:
>Here's a question maybe someone out there can answer:
>Why isn't it possible to completely restore a recording: for example, 
>to removeall extraneous noise (hiss, clicks, coughs)
>

I recall seeing something on TV (PBS?) about the recording restoration
lab at the New York Public Library.  They have loads of equipment to
do just this.  From what I remember, they spend most of their time
restoring old cylinder and 78 recordings.

kurt

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tody@noao.arizona.edu (Doug Tody X217) (07/21/88)

> >In article (Paul Gallagher) writes:
> >Here's a question maybe someone out there can answer:
> >Why isn't it possible to completely restore a recording: for example, 
> >to removeall extraneous noise (hiss, clicks, coughs)

It isn't possible to completely restore old recordings given current signal
processing technology and algorithms, but the following is a recent
development I found interesting.  This is a new line of CD's by Phillips
called "Legendary Classics".  Here is a quote from the liner notes in one
of my disks:

	Historical recordings by such legendary musicians as Ravel, Casals,
	Prokofiev, Van Beinum, Souzay, Oistrakh, and Richter, now lovingly
	restored to their original majesty thanks to Sonic Solutions' NoNoise
	micro-technology and Philips remastering and digital expertise.

		    The Artistry of the Past Now Made Perfect
	For Philips exclusive Compact Disk Collection of Legendary Classics

Well, of course it isn't perfect, but it is the most interesting commercially
available development I have seen in this area.  The difference in the sound
is very noticeable - doesn't mean you will like it though, many people won't.
There was a review of the technology in a recent Grammophone...  

Here is a brief description of the process from the liner notes before me:

	...Developed ... at Sonic Solutions, in San Francisco, Calif...
	NoNOISE can remove surface noise, tape hiss, clicks, and pops and
	other unwanted noise without affecting the original.

	...The digital data is then transferred to large computer disks and
	engineers at Sonic Solutions assess the problems, using special
	analytical programmes...

	If the recording contains clicks and pops, they employ a programme
	which incorporates techniques developed in artificial intelligence
	research [I'm just quoting this, don't blame me...].  This identifies
	the clicks or pops and recreates sound to replace the area they
	occupied.  Since the area is reconstructed rather than removed, the
	precise duration of the original performance is preserved.

	To reduce surface noise or tape hiss, ... analyze the spectral
	composition of the underlying noise floor.  Over 2000 points in the
	audible spectrum are measured to yield an accurate estimate of
	the unwanted noise.   This is then used by a special computer
	programme to perform "micro surgery" on the sound to reduce the
	noise without affecting any subtlety of the original.  Over 53
	million separate computations...  [etc.]

This is rather overstated, but an interesting experiment nonetheless.
I have only one such disk thus far - it is very good sound for such an
ancient recording - 1928, 1932, 1938, all mono (the Ravel and Prokofiev disk).
Unless you are interested in these ancient performances, however, any well
recorded modern performance is going to provide much better sound.

	Doug Tody
	NOAO, Tucson

strong@tc.fluke.COM (Norm Strong) (07/21/88)

In article <4867@vdsvax.steinmetz.ge.com> vdsvax!thearlin@steinmetz.UUCP (Thearling) writes:
}
}>In article (Paul Gallagher) writes:
}>Here's a question maybe someone out there can answer:
}>Why isn't it possible to completely restore a recording: for example, 
}>to removeall extraneous noise (hiss, clicks, coughs)
}>
}
}I recall seeing something on TV (PBS?) about the recording restoration
}lab at the New York Public Library.  They have loads of equipment to
}do just this.  From what I remember, they spend most of their time
}restoring old cylinder and 78 recordings.
}
A company named Sonic Solutions has come up with a rather complicated computer
program for removing noise, etc from old recordings.  It doesn't operate in
real time; in fact, it takes all night to clean up one side of a 78 at a rate
of 54 million computations per second.  (sounds fast to me.)

What do they call this process?  No Noise, of course.
-- 

Norm   (strong@tc.fluke.com)

mike@rbdc.UUCP (Mike steel) (07/28/88)

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