Izotope Rx Sample Rate
Russell McClellan
Batch Processing allows you to automate processing on groups of files, or apply processing from multiple modules to files. This can save hours when repairing files that require the same processing, or even something as simple as converting audio files to the same format, sample rate, etc. Avoid using mediocre sample rate conversion algorithms that are often found in video editing software, or basic DAWs like Pro Tools, Logic, etc. IZotope RX has great sample rate conversion, and most mastering engineers have “mastering grade” sample rate. At iZotope, we’re obsessed with great sound. Our intelligent audio technology helps musicians, music producers, and audio post engineers focus on their craft rather than the tech behind it. We design award-winning software, plug-ins, hardware, and mobile apps powered by the highest quality audio processing, machine learning, and strikingly. Apr 25, 2016 This video will help you understand the relationship between the number of bits and dynamic range in digital audio recordings. Think you're a studio master? Take the free iZotope. Jul 15, 2019 Standard sample rate: 44.1 kHz. The most common sample rate you’ll see is 44.1 kHz, or 44,100 samples per second. This is the standard for most consumer audio, used for formats like CDs. This is not an arbitrary number. Humans can hear frequencies between 20 Hz and 20 kHz.
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- Jul 15, 2019 In most DAWs, you’ll find an adjustable sample rate in your audio preferences. This controls the sample rate for audio in your project. The options you see in the average DAW—44.1 kHz, 48 kHz—may seem a bit random, but they aren’t! The sample rate determines the range of frequencies captured in digital audio.
- The analog (reconstructed) waveform is plotted in blue, while digital sample values are white dots. Let's now resample it to 22.05 kHz with a high-quality linear-phase SRC algorithm (RX 4, default settings). You can see how both sample values and true peak values (peaks of the analog waveform) have increased by over 0.5 dB.
In the last few years, a number of different countries have passed laws regulating the loudness of audio in television and other broadcast mediums. Surprisingly, loudness is a difficult concept to capture with a simple technical specification. Current regulations set limits for a number of different audio metrics, including overall loudness, maximum short-term loudness, and the true peak level of a signal.
What are true peaks?
To understand how true peaks differ from sample peaks, we have to go back to the basis of digital audio: the Sampling Theorem. This theorem states that for every sampled digital signal, there is only one correct way of reconstructing a band-limited analog signal into a digital one such that the analog signal passes through each digital sample. Digital-to-analog converters try to approximate this correct analog waveform as closely as possible. For more details on this fascinating theorem, we recommend this video from xiph.org.
Some audio editors are able to display the digital samples and an approximation of the corresponding analog waveform. In iZotope RX, both of these signals appear when you zoom far enough in. The blue line represents the analog signal, while the white squares are the digital samples.
In RX, you can click and drag on an individual sample to change it and see how the analog signal reacts. For example, if you move a single sample very far, we can see that a large amount of ripple appears in the analog signal around that sample.
It’s clear that the analog signal’s peak is quite a bit higher than the highest digital sample. The highest point the analog signal reaches is called the true peak while the highest digital sample is called the sample peak. Since a digital signal has to be converted to an analog signal to be heard, the true peak is a much more sensible metric for the peak level of a waveform.
It turns out that for real audio signals, quite often the true peak is significantly higher than the sample peak, so it’s important to measure carefully.
How are true peaks detected?
BS.1770, the international standards document used as the base for regional loudness specifications, gives a suggested algorithm to detect the true peak level of a digital signal. This algorithm is a relatively simple one: first, upsample the signal to four times its original sampling rate, and then take the digital peak of the new, upsampled signal. We can perform this algorithm manually in RX: first, open the “Resample” module and select a sample rate four times the original rate, then open the waveform statistics window and check the sample peak level. Here’s what the test signal above looks like after it has been upsampled to four times its original rate:
As you can see, after upsampling, the true peak level is now very close to the sample peak.
Of course, the RX waveform statistics window already provides the true peak level, so you don’t have to perform these steps by hand.
While this algorithm is quite good, there are two major ways that errors can occur. First, no upsampling algorithm can ever be perfect, so either overshoots or undershoots can occur during the upsampling process. This problem can be helped by using a high-quality upsampling algorithm. Second, the true peak may still be between samples even after the upsampling happens. This problem can be ameliorated by upsampling at a higher ratio.
How can we measure the quality of a true peak meter?
While most true peak meters follow the same basic algorithm as the one described in BS.1770, they can vary significantly in two dimensions: the quality of the upsampling algorithm, and also in the ratio of upsampling. BS.1770 includes a description of a simple upsampling algorithm, but many true peak meters actually perform more accurate upsampling than required by the specification. Also, many meters upsample by more than the required four times. This means that true peak meters can vary significantly in the accuracy of their output.
How can the quality of a meter be measured? One way is to create a synthetic signal that is difficult to meter accurately, but has a mathematically known true peak. This way, we can compare the meter’s reported true peak to the true peak we calculated ahead of time, and any difference can be attributed to meter error.
Testing meters with single impulses
One simple signal with a known true peak is a digital impulse, a signal with all samples at zero except for a single sample at a non-zero value. We can see the analog waveform this creates by looking at it in RX:
It turns out that the analog waveform for a digital impulse is a well studied function called the sinc function and has a simple mathematical expression: . Also, the true peak is the same as the sample peak at . This isn’t an incredibly useful signal for testing true peak meters, since even a bad true peak meter that only looks at the sample peak without upsampling will get the correct answer.
However, knowing the mathematical expression for the analog signal allows us to shift it in time to create a more interesting signal. Consider a signal the same function with a time offset of a fraction of a sample, say , i.e., . This signal should still have a true peak of , since time shifting an analog signal will not change its analog peak. However, the sample peak will be lower, since the true peak no longer sits exactly on a digital sample.
We can use Python, NumPy, and scikits.audiolab to create a wave file with this shifted sinc signal:
Then, we can open it in RX to see the digital samples and analog waveform:
As we can see, the analog waveform is the same, only shifted in time. However, now the sample peak is a few decibels lower than the true peak. We set , so the true peak is or dB. The sample peak is the sample immediately before the true peak, which using our formula above is or around dB, a difference of over two decibels from the true peak!
Since we know the exact true peak level of this signal, we can use it as a test of a true peak meter. It’s fairly difficult to measure, because a sinc function contains information at all frequencies up to the Nyquist frequency, making it difficult to upsample accurately. Also, the peak is located at a fraction of , so even perfect upsampling by four would not catch the true peak. You can download this shifted sinc test file here.
Testing Overshoot: Sine Sweeps
Another good test for true peak meters is a sampled sine sweep at a known amplitude. The true peak of this waveform will just be the amplitude of the sine sweep, but many meters will report a higher true peak because of errors in the upsampling algorithm. Like the sinc function, the sine sweep is difficult to upsample accurately because it has information at all frequencies. We can generate a sine sweep with the following NumPy code:
You can download the sine sweep file here.
How good is the example algorithm specified by BS.1770?
Now that we have a few techniques for measuring the quality of true peak detection algorithms, let’s put these to work in evaluating the example algorithm provided by BS.1770.
The upsampling algorithm is a simple one, based on upsampling by four, interpolating with a specific kernel. For more background information on upsampling, please see this reference. The coefficients of the kernel are given in the BS.1770 specification, and looks like this:
If we save this kernel as a wave file we can use RX’s Spectrum Analyzer to visualize the frequency response of this kernel:
Here, the cutoff frequency is a quarter of the sampling rate, or 6 kHz. The ideal filter would be perfectly flat below this frequency, and then drop immediately down to dB above it. Real world resampling filters have to make tradeoffs and cannot achieve this.
As we can see, there is a fairly significant amount of ripple in the passband (below roughly 5 kHz), which may indicate that the detector will overshoot at certain frequencies. Indeed, applying this detector to our sine sweep test signal, which has a true peak level of dB, results in a measured value of dB, an error of dB.
Also, the kernel is not very steep at our cutoff frequency. This indicates that for signals with a lot of high-frequency content, such as our sinc test signal, the filter may significantly undershoot. Indeed, for our shifted sinc test file, which also has a true peak of dB, the BS.1770 detector results in a measured value of dB, an error of dB. So, even compliant meters can have fairly significant errors in their true peak detection.
Extra credit: How high can true peaks get?
We’ve now seen several signals that have true peaks higher than their sample peaks, even by more than a decibel. Is there any limit to how much higher the true peaks can be than the sample peak? This is an interesting question because if there were some limit than we would have a worst case bound of how much error any given true peak meter could have.
Unfortunately for meters, it turns out that there is actually no limit to the difference between sample peaks and true peaks.
Plan of the Proof
To show that true peaks can become arbitrarily high, we’ll explore a pathological waveform where we can make the true peak as high as we want, by adding more samples. This particular example was discovered by iZotope colleague Alex Lukin, and the rigorous proof that it had an unboundedly high true peak was found by Aaron Wishnick.
The pathological waveform we are interested in is a series of alternations between and , followed by silence. We’ll show that by adding more alternations, we can make the true peak as high as we want to.
We can start to get a feel for this waveform by manually dragging samples around in RX. Here’s what it looks like after three alternations of and :
As you can see, one true peak is already higher than the sample peak of , and it’s exactly halfway between samples. Using RX’s waveform stats window, we can see that after three alternations the true peak is dB, while the sample peak is or dB. It turns out that by adding more alternations of and , we can make the true peak even higher. Here’s what it looks like with ten alternations:
Using waveform stats, we see that the true peak is dB, while the sample peak is the same at dB.
In order to prove that we really can make the true peak as high as we want, we’ll have to dig into some of the math.
Detailed Proof
For convenience, let’s call the time of the last sample time , so that the alternations of and extend back into negative time. Also for convenience, let’s assume our sampling rate is (this will make the math a bit easier). Judging from RX, this will put the true peak at time , half way between the last and the first .
So, we need to find an equation to tell us the value of the analog waveform at time . For this, we can use the Shannon interpolation formula:
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Where is our sampled signal at time , is the number of alternations and is the analog waveform at time . Since we are interested in , our equation becomes
We know from trigonometry that is positive if is even, or negative if is odd. We can express this as . So our equation becomes
Now, we plug in the fact that our signal consists of alternations between and , ending at at time 0. Note that when is even, and when is odd, since it alternates every sample. We can express this as . So, our equation simplifies to
Now, note the two terms cancel:
This is a formula for the analog level at time that only depends on the number of alternations, .
We can plot this series using Wolfram Alpha, and note that the sum diverges. We can also recognize this as a general harmonic series, which all diverge.
Knowing that the series diverges means that the more terms we add the more alternations of and , the higher the true peak will be. There is no limit to how high we can make the true peak, if we have enough alternations of and . However, since the signal is either , , or at all samples, the sample peak is always . So, knowing the sample peak doesn’t tell you much about the true peak, at least for these pathological signals.
With their hefty low–frequency content, vocal plosives are obvious as the blobs at the bottom of the spectral display.
The latest version of iZotope’s RX adds some interesting features — but do they have musical applications?
Restoration software of a kind which is relatively easy to use and which gives decent results is a comparatively new sector of the music software market. Someone will tell me that the DeNoise module in Sonic Solutions was probably in the vanguard here, but my own first encounter with this class of tool was CEDAR Retouch, fitted as an optional extra in the SADiE system which we used to record, edit and master classical recordings a decade ago. It was expensive, but invaluable: recording engineers’ nightmares such as piano pedal thumps, piano stool creaks, even lip smacks and the occasional cough no longer demanded a re–take, but could be eliminated, or substantially reduced, in post–production.
I originally bought iZotope RX2 to do some fairly heavy restoration work on a series of 1970s live operas that I was remastering for issue on DVD and accompanying CD. Sod’s Law dictated that the job came in just after I’d sold my SADiE system, and the built–in Spectral Cleaning facility in Magix’s Sequoia could not do all that was needed. Other offerings were beyond the budget, so RX2 fitted the bill perfectly, and I still think that the Advanced version is a whole lot of professional software solution for a relatively small outlay. Only after those projects were completed did I begin to realise how tightly woven into my mastering approach it would become.
In For Repairs
I have now been using iZotope RX2 since it was released in 2010. Apart from the DAW itself, it is the one piece of software that I have found to be indispensable, and I have used it on pretty much every mastering session. RX can play almost any file, and has frequently opened recalcitrant formats which had standard DAWs flummoxed. It has exceedingly good sample–rate conversion (with MBit+ dithering) and, of course, it can repair sonic damage, ameliorating those bad–luck moments in live recordings and unnoticed horrors in studio recordings which cannot be recalled and undone. Even with projects that did not call for large–scale restoration work, it was good to be able to identify such momentary irritations as vocal glitches, the base of a mic stand being kicked, the studio cat, mic capsule distortions, clunks, coughs and so on, and quickly brush them aside. And that was only the Spectral Repair feature, which provides a highly informative visual interface for spotting and addressing these problems.
In my mastering suite, with its revealing acoustics and speakers with extended bass response, I often encounter vocal plosives and very fast transient clicks that have been missed by the client and the engineer. The pictures show how these look in the RX4 main display: the click is shown in Linear mode, as digital clicks have content across the whole frequency spectrum, while the vocal pop is shown in Extended Log mode because plosives have a great deal of low–end content. Each of these issues took just a few seconds to eliminate entirely in RX4: lasso the problem area, press ‘R’ for repair, and the offending item is attenuated to inaudibility. More complex problem sounds have more complex repair modes, but with a little experience, they are barely any more difficult to implement.
A rogue click is clearly visible in RX4’s spectral display.
It’s worth noting that iZotope present RX as software that can find application across all kinds of audio work. However, although many of the features of RX that I find useful when working with musical content are also useful for non–music audio work, the converse doesn’t always apply. In other words, there are some tools in RX which are very useful in non–musical applications, yet have less immediate use in music production. iZotope themselves sort the modules according to function, into Restoration, Production and Utility groups.
Three: The Magic Number
Late in 2013, iZotope released version 3 of RX. Not only did RX3 sport an entirely new, and very much more ergonomically optimised user interface, but it also included interesting new modules in all of the functional groups, and several previously Advanced–only features were incorporated into the much more affordable Standard version. As these included the excellent sample–rate conversion algorithms, this made the standard version of RX very much more attractive to a wider base of music engineers. Hugh Robjohns reviewed RX3 in full in the February 2014 issue (www.soundonsound.com/sos/feb14/articles/izotope–rx3.htm), so I don’t want to repeat too much of what was said then here, but it is worth re–emphasising the gist of the conclusion of that review, which was that RX3 is a worthwhile investment for anyone involved in professional music production, and that the upgrade from RX2 was also, as they say, a no–brainer.
In RX4 another advanced module, the Dialogue Denoiser, has made the same migration to Standard. iZotope are wise to have this divide, as not every engineer will need the Advanced–only functions, which are often quite specialised — and as I think the Advanced version is good value for money, this makes the Standard Version a bit of a bargain.
Pillar To Post–production
If RX3 represented quite a large leap forward from RX2, then RX4 is a smaller step in the same direction. New features include Clip Gain and a Clip Leveler, which do pretty much what their names suggest; less standard, and potentially more interesting, are features and modules such as RX Connect (see box), EQ Match and Ambience Match.
I mentioned earlier that some of RX’s existing features are targeted mainly at non–musical applications, and in fact, the two new modules in RX4 probably fall into this category. Ambience Match is not, despite the name, a convolution reverb, or indeed any kind of reverb. And while EQ matching — the idea of capturing the frequency responses of source and target tracks, and computing an EQ curve to make the former sound like the latter — arguably has a place in mastering and music production, the EQ Match feature in RX4 is so basic as to be of limited use. It is nothing like as sophisticated as Harbal (www.soundonsound.com/sos/feb13/articles/harbal-3.htm), nor even the Matching EQ feature in iZotope’s own Ozone mastering software. In the latter, the capture process produces visual curves for the overall EQ and difference EQ changes which can be overlaid to allow them to be compared and, if necessary, modified. EQ Match in RX is a greatly simplified form of this. The screenshot shows the UI dialogue, and the manual is quite succinct: after you have opened the EQ Match module, it tells you to “make a selection in a file; click Learn; make another selection; click Process.”
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RX4’s EQ Match feature is more basic than its counterpart in iZotope’s own Ozone mastering software.
For musical needs, I would say that this implementation falls short of being really useful. Most music engineers would want much more information and much more control over EQ changes applied to their tracks. But as I’ve indicated, this module is probably more likely intended for certain non–musical applications where such immediacy (and very good results given the simplicity) is an advantage in itself. I can illustrate this better by introducing the Ambience Match module at this point and showing how they operated together when I revisited an audio–book project I worked on last year.
Voices & Choices
The main recording for the audio book, which featured a number of different voices, was done in a London hotel. But then sometime later editing changes were made to the text itself, and so certain passages of the book had to be re–recorded. Some of this took place in my own small studio in Norfolk, using the mic with which we’d recorded the originals; but one particular reader could not travel that far, so recorded the changes at a more convenient local facility with a different microphone and sent me the results to be edited in. At the time, this gave me an awful lot of extra work to do. There were clearly mismatches of vocal tone and also background ‘room tone’ (low–level ambient sound), and though I could EQ the vocal sound to minimise the differences, the only way I could make sure that there was no clearly audible difference in the rooms was to cut a small piece of room tone from the very beginning of the original recording, edit it to a usable length and mix it in, ducking it with the vocals. It worked just about well enough, but it took an awful long time.
For the purposes of this review, I revisited this nightmare with RX4 and it took me 15 minutes. Though the voices were the same, the use of different spaces, placements, mics and preamps meant there were tonal differences between the original and later recordings. The original recording was warmer and smooth, the re–recording to edit in was less so in both regards — but the RX4 EQ Match module made a very passable attempt to live up to its name, and I think I would have been happy to use the result had I had the chance to do so.
The new Ambience Match feature is designed to ensure that room tone can be made consistent when editing together recordings from different sources.
The room tone was very different between the two versions: although the original recordings were not exactly noisy, there was a very specific ‘hotel room’ sound to the silence, with a faint air–con motoring away somewhere in the basement. The re–recordings, made in recording studios, had much quieter, almost silent backgrounds, and this was easily perceptible when the original section segued into the edit. This is where Ambience Match came in. As you can see from the screenshot, it has the same minimalist interface as EQ Match. Fingerprinting the room tone from the original and adding it to new edits was very easy, and it took just a couple of experimental passes to get the level right. I had hoped that Ambience Match was going to be rather more — conceptually, it’s really just the Denoise module working in reverse, as the manual almost admits — but fitting horses to courses enabled it to show its proper strength. It also found a use in classical editing: many producers still insist that recordings do not fade to digital silence between movements and between separate pieces, so the editor has to edit in room tone recorded at the beginning of the session to give the illusion of a continuing live recital (ha!). Editing virtual silences together is a pastime for the seventh circle of Hell, so Ambience Match could be a real boon there.
Conclusion
As I have made clear, I find iZotope RX4 indispensable in almost every post–production project, including mastering and its manifold responsibilities. I also think the asking price is not a great deal for a professional facility to pay for a professional product, and that the ‘missing’ features of the Standard version that allow it to be offered pretty much at bargain price are less likely to be missed by music users. So RX4 is a great upgrade for users of RX2, and a great buy for those who are yet to feel the love at all. But is it a good upgrade for present users of RX3? I think it all depends on just how much use can be made by the purchaser of the half–dozen or so substantial new features. For those in film and speech post–production, this might be all of them; for some, like myself, who specialise in music but have a serious sideline in speech and restoration, that might be two or three; but for some music–only facilities, it might not be quite enough to justify the move just yet.
Only Connect
It is possible to use iZotope RX in two different ways: as an adjunct to a DAW, or in stand–alone mode. Even in RX2, there was already a facility which enabled Spectral Repair as a plug–in from within a DAW. In RX4 this has been replaced by a more fully featured ‘round trip’ capability called RX Connect. The idea is that, without leaving your DAW, you can either send a clip from your DAW for Analysis in RX (a one–way ticket) or you can send it for Repair and then return it to the DAW (a two–way ticket). One issue that can arise is that if your DAW does not ‘surrender’ its audio channels to RX when that is operating, then nothing routed through RX can be monitored. Enter an ingenious solution called RX Monitor, which gets around this problem by operating in the DAW as a virtual instrument through which the RX output can be played via the DAW’s non–surrendered channels.
I tried RX Connect in a mastering context, and it worked as advertised, but because there were a few menu items to negotiate and you need to pre-open the stand-alone version of RX, I found that it was just as easy for me to minimise the DAW, open RX in stand-alone mode, and work directly on the WAV file. Things changed dramatically, though, when I was working on a classical editing project where the fragments of music to be edited together were drawn from up to 100 different takes, hence 100 different WAV files. When doing this kind of work in the past, the technique I use now when mastering would not have been viable, as it would have meant opening all of those 100 different files, rather than the single one being worked on in mastering. Instead, I would deal with noises and suchlike by noting their time position in the overall piece, compiling the final edit and only then going to RX. It never occurred to me that there could be a better way — but this is where RX Connect starts to make much more sense. A process that is relatively unwieldy when compared to opening the stand-alone version for occasional work on a single WAV file becomes the clear winner when compared to opening and searching in 100 or more separate audio files! And also, as often happens, what seems a bit awkward when you are consciously concentrating on each step in the process becomes second nature and much easier as familiarity and muscle memory kicks in. Of course, there was a time when making up a DDPi file seemed like a lot of work..
Pros
- Better integration for those who like to carry out their restoration tasks within a DAW.
- EQ and Ambience Match can help when you need to edit together recordings made under different circumstances.
- Still offers excellent value for money.
Cons
- The new features are arguably more useful in post–production than in music work.
Summary
RX4 is a worthy update to perhaps the best–value restoration package on the market, though it perhaps won’t be an essential one for users who work only with music recordings.
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