Back to overview Documentation version 9.23
Automatically learning noise and hiss remover.
Some radio stations have a problem with constant sounds, such as a 50/60 Hz hum from a bad cable (which can be hard to find), a high pitch tone from a fan or airconditioner, a constantly present hiss etc. PNR Noise & Hiss can learn what the disturbing sound sounds like, and then remove it.
For constant tones, the removal is nearly perfect, with nearly no side effects, even if a tone is as loud as the actual programming. For non-constant tones, including hiss, PNR can reduce it by a few dB without causing noticeable artifacts.
See this YouTube video for an example of how to set it up and what it does:
How it works:
- First, we measure at least a few seconds of silence (noise only, by enabling Collect Data) to determine what the noise sounds like.
- From the measured audio, after filtering out the lowest and highest values using Ignore lowest and Ignore highest, the minimum level, the average value, the medium value (at position Minimum Median Position) and the variance are determined.
- Minimum Multiplier, AVG Multiplier, Link error '2872' and Sigma (variance multiplier) are used to determine how much audio will be removed. These values may be changed after the measurement.
- Removing audio begins immediately after Collect Data is disabled. Use the Difference to check that (almost) no real audio gets removed.
The average value and sigma (variance) are used to determine how much more audio should be removed than the minimum. If this is increased too much, artifacts will become more audible.
Main PNR settings.
Enables PNR Noise & Hum removal.
- After Declipper (Declip first)
Perform Dehummer after the Declipper.
If your material is clipped first and then noise/hum is added, for example if you play clipped CD's on a system that has a hum, the hum needs to be removed first, and declipper should be done afterwards. In that case, leave this setting off.
But, if for some reason the clipping happened after the noise/hum was added, then you can enable this setting to declip first, and remove the noise and hum afterwards.
- Minimum Multiplier
Multiplier for the minimum amount of audio measured.
For completely constant tones, using 100% here will completely remove the sound, lower values will always reduce less. Normally 100% is a good value here.
- AVG Multiplier
Multiplier for the average level that was measured.
- Sigma (variance multiplier)
Multiplier for the sigma (variance) level.
- Sigma Steepness
Steepness when going from Minimum to Sigma filtering behavior.
ANALYSIS STEP panel
The settings here are [b]only[/b] used during analysis!
- Ignore lowest
Percentage of lowest measurements to ignore.
- Ignore highest
Percentage of highest measurements to ignore.
- Collect Data
Enables collection of PNR data.
Enable this on moments of silence (with the disturbing sounds present), so the filter can learn what to remove. You might need to click RESET ANALYSIS DATA to remove data that was collected earlier. This step needs to be performed at the correct Sample rate, Latency, Link error '264' and Input gain setting - when any of these settings are changed, the learned information becomes unusable, and the filter is disabled until either the settings are restored or a new learning stage has been performed.
- RESET ANALYSIS DATA
Clears all the learned information.
Always press this when a new Collect Data step will be performed with changed audio (different disturbing sounds).
Continuous Learning (EXTREME CPU LOAD) panel
Dynamically adjust the Dehummer behavior based on the input.
Note: This is not necessarily a good idea for good audio quality, it's more intended at forensics uses. For example, if you want to filter out the sound of a driving car, which slowly changes in sound, it can help to make the Dehummer learn continuously.
On music this will sound bad, so don't use it on that.