Filter Selection
Last updated
Last updated
On this page, you select the type of filter/equalizer that you want to train on.
‘Filter’ generally refers to a cut-only device, whereas an equalizer can either boost or cut.
FREQUIA only allows you to train on one filter or equalizer at any given time. The rationale for this is that very few people can correctly identify +/- 1dB changes made to audio signals, and even fewer can consistently achieve this in Absolute Identification mode.
A High-pass Filter (HPF) passes (doesn't boost or cut) frequencies ABOVE the selected frequency, whereas a Low-pass Filter (LPF) passes frequencies BELOW the selected frequency. A high Q value may boost certain frequencies, even though there is no gain applied.
The parameters of High/Low-pass Filters that you can train to identify are Frequency and Q (these filters do not have a Gain parameter).
If you choose to train on this type of filter, FREQUIA will randomly choose between a High-pass or a Low-pass filter during training.
Shelving equalizers boost or cut all frequencies above or below the selected frequency. There are two types of Shelving Equalizers: Low Shelf and High Shelf. A Low Shelf boosts or cuts all frequencies BELOW the selected frequency. A High Shelf boosts or cuts all frequencies ABOVE the selected frequency.
The parameters of Shelving Equalizers that you can train to identify are Frequency, Gain, and Q.
If you choose to train on this type of equalizer, FREQUIA will randomly choose between a High-shelf or a Low-shelf during training.
Parametric Equalizers boost or cut frequencies symmetrically around a selected center frequency. Gain controls the amount of boost or cut, and Q controls the bandwidth of the boost or cut.
The parameters of a Parametric Equalizer that you can train to identify are Frequency, Gain, and Q.
Bandpass Filters pass all frequencies within a certain range and cut all others. In reality, these filters cut all frequencies except those at the very center.
The parameters of a Bandpass Filter that you can train to identify are Frequency and Q (these filters do not have a Gain parameter).
Bandstop Filters cut all frequencies within a certain range and pass all others.
The parameters of a Bandstop Filter that you can train to identify are Frequency and Q (these filters do not have a Gain parameter).
