Ήδη έχουμε φτάσει στην έκδοση 2.5 που από ότι λέγεται είναι και η καλύτερη. Και μία άποψη της Sonic Studio για το τι ακριβώς κάνει κατά το Processing:
"The first task is that the audio file, represented as digital data, must be read off the media and into memory. This requires the audio player to guarantee (as best it can) the audio will be read from the disk in time. The player needs to deliver the audio samples to the Hardware Interface not only on time but also synchronized. Otherwise, we may hear clicks, dropouts, phase, and balance problems. Sonic addresses this using optimized file handling routines. We do not look at latency as an issue in a home audio reproduction system unless it's being synchronized with video.
Once the audio is in memory, it needs to be converted to a format the computer can "understand". Current audio formats for uncompressed audio use a 16 or 24 bit sample and this must be converted to the IEEE floating point architecture in use by most computers today. This conversion can introduce noise into the audio signal. Should we truncate, round, scale or perform some combination to achieve the best sounding result? This conversion occurs on input from the disc and on output to the hardware interface. Based on our experience, we sometimes find that textbook math does not mean the best sounding math.
The next stage is the gain structure and processing that may take place inside the audio engine. When you adjust the slider to control the volume a gain process is applied to the audio signal. Even when the gain is at full volume processing may take place that effects the sound. In the Sonic Studio Engine we perform all calculations using 64 bit extended floating point math. This allows us a full 56 bit mantissa which allows us to keep the noise levels below the 24th bit found in high resolution audio. When any processing is applied it is important to redither the sounds to mask the effects of all the rounding and noise that were previously introduced. To address this problem, SSE comes with two dither algorithms which are optimized for use with Amarra. Perhaps as important as the underlying math is the efficiency in implementation as each operation has the possibility of increasing the noise."
