One type of (low-pass) filter which I had learned about some time ago, is a Sinc Filter. And by now, I have forgiven the audio industry, for placing the cutoff frequencies of various sinc filters, directly equal to a relevant Nyquist Frequency. Apparently, it does not bother them that a sinc filter will pass the cutoff frequency itself, at an amplitude of 1/2, and that therefore a sampled audio stream can result, with signal energy directly at its Nyquist Frequency.
There are more details about sinc filters to know, that are relevant to the Digital Audio Workstation named ‘
QTractor‘, as well as to other DAWs. Apparently, if we want to resample an audio stream from 44.1 kHz to 48 kHz, in theory this corresponds to a “Rational” filter of 147:160, which means that if our Low-Pass Filter is supposed to be a sinc filter, it would need to have 160 * (n) coefficients in order to work ideally.
But, since no audio experts are usually serious about devising such a filter, what they will try next in such a case, is just to oversample the original stream by some reasonable factor, such as by a factor of 4 or 8, then to apply the sinc filter to this sample-rate, and after that to achieve a down-sampling, by just picking samples out, the sample-numbers of which have been rounded down. This is also referred to as an “Arbitrary Sample-Rate Conversion”.
Because 1 oversampled interval then corresponds to only 1/4 or 1/8 the real sampling interval of the source, the artifacts can be reduced in this way. Yet, this use of a sinc filter is known to produce some loss of accuracy, due to the oversampling, which sets a limit in quality.
Now, I have read that a type of filter also exists, which is called a “Farrow Filter”. But personally, I know nothing about Farrow Filters.
As an alternative to cherry-picking samples in rounded-down positions, it is possible to perform a polynomial smoothing of the oversampled stream (after applying a sinc filter if set to the highest quality), and then to ‘pick’ points along the (now continuous) polynomial that correspond to the output sampling rate. This can be simplified into a system of linear equations, where the exponents of the input-stream positions conversely become the constants, multipliers of which reflect the input stream. At some computational penalty, it should be possible to reduce output artifacts greatly.
Continue reading A Note on Sample-Rate Conversion Filters