FLAC ENTROPY OPTIMIZER
XiFEO optimizes the entropy of high resolution audio files to make sure that a standard FLAC encoder achieves in average a 30% – 50% higher compression rate.
This is useful for mobile high resolution audio players with limited memory or streaming services that need to use their available bandwidth efficiently.Add to cart
- Windows 7 – 10 / 32 & 64 Bit
- Mac OSX Lion 10.7.3 – Sierra 10.12.x
64Bit High Precision Audio Engine
Input Audio Formats: FLAC, ALAC, WAV, AIFF,
Output Audio Formats: FLAC
SNR Analysis to identify the number of bits submerged in noise
Identifying the highest frequency components containing music
Apply dithered bit truncation and out of band noise filtering
Metadata transfer (album, title, artist, cover, etc.) between all file formats that include metadata
Multi-Threading to allow the conversion of several audio files in parallel
Batch processing with freely configurable output file names
The test version is limited to a one minute transcoding per audio file
The activation key allows three parallel activations on Windows and/or MacOS X
XiFEO can be fully tested before purchase.
The activation allows 3 parallel installations. In fact, it is possible to use the Windows and MacOS X Version in parallel by just using one activation key.
WHY SHOULD I FLAC ENTROPY OPTIMIZE MY HIGH RESOLUTION AUDIO FILES?
A FLAC encoder becomes much more efficient if we reduce the entropy (noise) of an audio file before it gets compressed.
The methods FLAC applies for lossless compression are based on the technology of “Sparse Sampling of Signals with Finite Rate of Innovation”.
A piece of an audio signal is approximated either by a simple polynomial or a linear predictive coding (LPC).
An audio sample sequence containing noise is not really a special signal of finite rate of innovation (FIR) that could be sparsely sampled without taking care about the residual error and therefore it is not enough to just encode the coefficients of the polynomial but also the residual error!
The residual error increases with the entropy of the data to be compressed.
Simply said, if we could reduce the noise then the FLAC encoder would operate much more efficient.
XIFEO’S GOAL IS TO REDUCE THE ENTROPY OF THE FILE IN A TWO-STEP PROCESS
Statistical Analysis of the bit-structure to find out how many LSB bits are just carrying noise.
All LSB-Bits that just contain real noise can be truncated by simply setting them to zero. The effect is a strong reduction in entropy.
During our tests, we learned that sometimes well dithered native high resolution audio files still have audio information within the 2nd LSB and therefore we could only throw away one bit to avoid losing any critical bit-depth.
Of course, any truncation asks for dithering which we apply.
An analysis that identifies the highest frequency components that still contain spectral information of the music to remove out of band noise.
As signal analysis theory tells us, filtering outside of the audio spectrum does not do any harm, even if we apply very long linear phase low-pass brick-wall filters.
So, if we have identified up to what frequency the highest spectral components of the music reach, we can just filter everything else above those frequencies because it is simply out of band noise.
We want to emphasize that this is not our invention. Individuals have already discussed similar compression schemes.
For XiFEO we added statistical algorithms that are able to find out whether a bit just contains noise. Furthermore, the algorithms are able to examine the spectrum to remove out of band noise efficiently.
Achievable Compression Factors:
XiFEO exhibits a variable compression rate depending on the number of bits that are allowed to be truncated and the amount of out of band noise.
In the case of very well recorded and dithered 192kHz / 24Bit native high resolution already FLAC encoded audio files it is difficult to achieve a high compression rate because then it would be at most possible to truncate a small number of bits achieving an average compression factor of maximum 1.7.
For more common 96kHz / 24Bit high resolution audio files, that additionally do not exhibit extreme fidelity, an average compression factor of around 2 is achievable.