As with medical diagnostics, the key to successful audio restoration lies in your ability to correctly analyze the subject’s condition. This can be a life-long, never-ending quest, constantly honing the ear to distinguish the noises and audio events that need to be corrected.

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Identifying Audio Problems. As with medical diagnostics, the key to successful audio restoration lies in your ability to correctly analyze the subject’s condition. This can be a life-long, never-ending quest, constantly honing the ear to distinguish the noises and audio events that need to be corrected. May 20, 2018 Open the audio file in the RX Audio Editor or send it via RX Connect. Open the Corrective EQ module Option+Shift+7. Engage a high-pass filter to remove the most apparent rumble and to make any other static filtering gestures before applying the De-noiser. NEW: Remove mouth clicks with Mouth De-click. Sensitive microphones can bring out mechanical noises of the mouth which can be very distracting. The new Mouth De-click module in iZotope RX 6 is a de-clicker that is finely tuned to detect and reduce mouth noises including clicks and lip smacks. Try Izotope RX. Use the denoiser to remove some of the broadband noise, and ride the volume, so you decrease the volume between the words. You can remove some of the splatters with spectral repair. Make a mono background atmosphere which sounds dry, which you can use to mask the rest of the rain sounds.

To get started, it’s important to identify the problems with your file and identify which tool(s) will give you the results you want. Let’s briefly look at how to examine your audio using the spectrogram and waveform display tools, then consider how to identify audio problems using these displays.

What’s the goal of using a Spectrogram?

RX has many different tools for removing noise and other audio problems. To get started, its important to identify the problems with your file and identify which RX tool or tools will give you the results you want. Hum and Buzz. Hum is usually the result of electrical noise somewhere in recorded signal chain. Apr 04, 2018  To remove hum, use the RX De-hum module. It works best when frequencies of the hum do not overlap with any useful transient signals. In some cases, electrical noise will extend up to higher frequencies and manifest itself as a buzz. Sounds like these can also come from fluorescent light fixtures, motors, and some on-camera microphones. Sep 23, 2014 Can’t be removed with an automated process (unlike broadband noise, hum, clicks, and crackles) Leave artifacts and/or damage the original audio when removed by most traditional audio-editing tools Fortunately, RX includes a number of ways to remove these noises. Begin by identifying the unwanted noise via the spectrogram.

The aim of any good visualization tool for audio repair and restoration is to provide you with more information about an audible problem. This not only helps inform your editing decisions, but, in the case of a spectrogram display, can provide new, exciting ways to edit audio, especially when used in tandem with a waveform display.

Hum

Hum is usually the result of electrical noise somewhere in the recorded signal chain. It’s normally heard as a low-frequency tone based at either 50 Hz or 60 Hz depending on where the recording was made If you zoom in to the low frequencies, you’ll be able to see hum as a series of horizontal lines, usually with a bright line at 50 Hz or 60 Hz and several less intense lines above it at harmonics. See the example below:

De-hum works best when frequencies of the hum do not overlap with any useful transient signals. You can learn more about the De-hum tool here.

Buzz

In some cases, electrical noise will extend up to higher frequencies and manifest itself as a background buzz. See the example below:

Hum-removal tools usually focus on low-frequency hum, so when the harmonics extend to frequencies above 400 Hz, the Spectral De-noise tool is often more effective at removing the problem. Mixmeister express alternative medicine.

Hiss and other Broadband Noise

Unlike hum and buzz, broadband noise is spread throughout the frequency spectrum and isn’t concentrated at specific frequencies. Tape hiss and noise from fans and air conditioners are good examples of broadband noise. In a spectrogram display, broadband noise usually appears as speckles that surround the program material. See the example below: 

Clicks, Pops, & Short Impulse Noises

Clicks and pops are common on recordings made from vinyl, shellac and other grooved media, but can also be introduced by digital errors, including recording into a DAW with improper buffer settings, or making a bad audio edit that missed a zero crossing. Even mouth noises such as tongue clicks and lip smacks fall into the clicks category. These short impulse noises appear in a spectrogram as vertical lines. The louder the click or pop, the brighter the line will appear. The example below shows clicks and pops appearing in an audio recording transferred from vinyl: 

The De-click tool can recognize, isolate, and then reduce and remove clicks like these.

Clipping

Clipping is an all-too-common problem. It can occur when a loud signal distorts the input to an audio interface, analog-to-digital converter, mixing console, field recorder, or other sound capture device. A spectrogram is not particularly useful for identifying clipped audio—for this you’ll want to work with a waveform display. As you’ll see in the image below, the clipping appears as “squared-off” sections of the waveform.

You can zoom in on a waveform and see in detail where the waveform has been truncated because of clipping.

The De-clip tool can intelligently redraw the waveform to where it might have naturally been if the signal hadn’t clipped. Sometimes, brickwall limited audio will also appear “squared off” when zoomed out, but this doesn’t necessarily mean it will sound as heavily distorted as clipped waveforms that have been truncated. You can zoom in to see if the tops of individual waveforms are clipped.

Intermittent Noises

Intermittent noises are different than hiss and hum—they may appear infrequently and may not be consistent in pitch or duration. Common examples include coughs, sneezes, footsteps, car horns, ringing cell phones, etc. The images below represent two different examples of these noises:

The Spectral Repair tool can help isolate these intermittent sounds, analyze the audio around them and attenuate or replace them.

Gaps and Drop Outs

Sometimes a recording may have short sections of missing or corrupted audio. These are usually very obvious to both the eye and the ear! See the example below:

Deleting the gap and then applying Spectral Repair to replace any missing audio can help fix these problems.

This page contains reference information about this module. For more information on how to use Denoiser see the Users Guide.

Denoiser is designed to reduce stationary noise, including broadband noise, in audio signals. Stationary noise can include tape hiss, microphone hum, power mains buzz, camera noise and other types of noise that do not change in level or spectral shape throughout the recording.

Training Denoiser:

Denoiser can learn the type of noise you want to remove from the recording to give you the best results. To train Denoiser, select a section of the recording that contains only noise and click Train. This will create a noise profile that Denoiser will use to process the recording. If you do not have a section of the recording that contains only noise, selecting a quiet region of the recording that contains mostly noise can also work.

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Note: The noise profile will be valid only for the currently selected FFT size, current sampling rate and number of channels. If either of these parameters changes, the noise profile should be re-collected with the updated parameters for accurate noise reduction results.

Noise Spectrum Display:

The Noise Spectrum display shows useful information during both playback and when the noise reduction process is being applied.

Color Legend

• Purple curve (Input) - spectrum of input audio signal

• Yellow curve (Output) - spectrum of denoised (output) audio signal

• Blue curve (Noise Profile) - equals learned noise profile + threshold elevation control

• White curve (Residual Noise) - desired noise floor after denoising, can be controlled by Reduction and Residual whitening controls (Advanced mode only)

Scrolling and Zooming - by grabbing and moving the horizontal and vertical rulers, you can adjust what part of the graph is shown. In addition, holding the pointer above a ruler and using your mouse wheel will zoom the display in and out.

Simple Mode controls:

• Algorithm - affects the quality and computational complexity of the noise reduction. This selection directly affects CPU usage.

• Noise Reduction (dB) - controls the desired amount of noise suppression in decibels.

• Artifact Suppression - helps minimize 'musical noise' artifacts introduced during the noise reduction process.

• Output Noise Only - outputs the difference between the original and processed signals (suppressed noise)

Advanced Mode controls:

Threshold (tonal/broadband) - controls the separation of noise and useful signal levels.

Higher threshold settings reduce more noise, but also suppress low-level signal components. Lower threshold preserves low-level signal details, but can result in noise being modulated by the signal. Threshold elevation can be done separately for tonal and random noise parts. A good default is 0 dB.

Reduction (tonal/broadband) - controls the desired amount of noise suppression in decibels.

Denoiser can automatically separate noise into tonal parts (such as hum, buzz or interference) and random parts (such as hiss). The user can specify the amount of suppression for these parts separately (e.g. in some situations it can be desirable to reduce only unpleasant buzz while leaving unobjectionable constant hiss). Strong suppression of noise can also degrade low-levels signals, so it's recommended to apply only as much suppression as needed for reducing the noise to levels where it becomes less objectionable.

Musical noise suppression - controls the reduction of artifacts known as 'musical noise'.

Musical noise is caused by random statistical variations of noise spectrum that cause random triggering of sub-band gates resulting in 'metallic' or 'space monkey' sounds. The control synchronizes triggering of noise gates in time and in frequency and makes gates sensitive only to larger sound events eliminating small random variations. Too high values of this slider can produce muffled sound and suppress minor details in the useful signal.

Residual Whitening - modifies the amount of noise reduction (shown by light blue curve) applied at different frequencies to shape the spectrum of the residual noise.

When residual whitening is zero, the suppression is uniform at all frequencies, as controlled by Reduction (tonal/broadband) sliders, and the suppressed noise has a similar spectral shape to the original noise. When residual whitening is maximal, the desired shape of suppressed noise floor is made close to white, so that residual noise has more neutral sound.

RX Advanced Only controls:

MNS algorithm - selects the smoothing algorithm for the removal of random ripples that can occur in the spectrogram when processing your audio. These sounds are referred to as 'musical noise' and can be described as sounding 'watery'.

The strength of smoothing is controlled by the 'Musical noise suppr.' slider.

• Simple algorithm performs independent noise gating in every frequency channel of FFT. Release time of sub-band gates is controlled by the Release control. This is a fast algorithm with small latency that is suitable for real-time operation.

• Advanced and Extreme algorithms perform joint time-frequency analysis of the audio signal which results in better quality and less 'musical noise' artifacts. These algorithms have higher latency and computational complexity.

FFT size (ms) - selects the time and frequency resolution of the processing. Higher FFT sizes give you more frequency bands allowing you to cut noise between closely spaced signal harmonics, or cut steady-state noise harmonics without affecting adjacent signals. Lower FFT sizes allow for faster response to changes in the signal and produces less noisy echoes around transient events in the signal.

Note: Whenever FFT size is changed, it's recommended that the user retrain the Denoiser's noise profile because the old noise profile was taken at a different FFT size and therefore becomes inaccurate.

Multi-resolution (checkbox) - enables multi-resolution for the selected algorithm type

When you select the 'Multi-resolution' checkbox, the signal is analyzed in real time and the most appropriate FFT size is chosen for each segment of the signal. This is done to minimize the smearing of transients and at the same time achieve high frequency resolution where it is needed.

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Note: The FFT size control does not have any affect in multi-resolution mode as the FFT resolution is selected automatically. The noise profile does not need to be re-learned when switching to Multi-resolution mode.

Knee sharpness - controls how surgical the algorithm's differentiation is between the signal and noise.

This slider controls the bending 'knee' softness in the denoising process. With higher values, transitions in the denoiser are more abrupt and can become prone to errors in the detection of the signal with respect to the noise. When the sharpness is reduced, the denoising becomes more forgiving around the knee, and applies less attenuation to signals that are only slightly below the threshold. This may result in a lower depth of noise reduction, but can also have fewer artifacts.

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Release (ms) - selects the release time of sub-band noise gates in milliseconds

Longer release times can result in less musical noise, but may also reduce or soften the signals initial transients or reverb tails after the signals decay.

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Note: The Release control is only available when the 'Simple' MNS Algorithm is selected.

Psychoacoustic suppression - enables a psychoacoustic model that dynamically controls suppression amount to facilitate the use of softer suppression where noise is subjectively inaudible. When noise in certain regions is calculated to be inaudible, this feature prevents any signal processing in these regions. This potentially reduces amount of processing done to the signal and may positively affect overall signal integrity. The position of the slider controls the influence of psychoacoustic model on suppression levels.

Note:When this slider is set to 0, the feature is turned off, and the amount of noise suppression is uniformly governed to the white curve in spectrum analyzer (more precisely - by the difference between the white curve and blue curve).

Harmonic enhancement - predicts a signals harmonic structure and places less noise reduction in areas where possible signal harmonics could be buried in noise. This aids in at least preserving high-frequency signal harmonics that may be buried and not detected otherwise. It can make the resulting signal brighter and more natural sounding, but high values of harmonic enhancement can also result in high-frequency noise being modulated by the signal.

Additional Denoiser Features:

• Noise Suppression Envelope - This feature allows for fine tuning of the noise suppression envelope with up to 26 edit points. This enables the user to customize the amount of noise reduction being applied across different frequency regions.

• Add an edit point - Left-click, displayed as gray box along envelope curve

• Remove an edit point - Right-click (CTRL click on Mac) or drag it outside the screen

• Envelope Show - This controls whether or not the suppression envelope points are visible or hidden. The modified envelope will always be applied even when edit points are hidden.

• Envelope Reset - This will remove all edit points.

• Envelope Smoothing- This controls the amount of interpolation between your suppression envelope points, allowing for sharper or more gradual envelopes.

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