To simplify this document we have grouped the topics and set them as questions and answers either as response, tutorial or axiom. Some months ago we published a comprehensive Q&A for an online forum and to avoid repetition we…
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Author's Note: We are grateful to Stereophile for the opportunity to address some frequently repeated technical questions appearing in comments to articles. Recently this has included misunderstandings about noise calculation, dynamic range, resolution, definition, music spectra, channel capacity, lossless processing and temporal aspects of digital channels.
Question: What is MQA?
Answer: In essence, MQA is a hierarchical method and set of specifications for recording, archiving, archive recovery and efficient distribution of high quality audio. Devised by long-term collaborators Bob Stuart and Peter Craven, it has been developed by MQA Ltd. [1]
One axiom is that, in audio, High Resolution can be more accurately defined in the analogue domain in terms of temporal fine structure and lack of modulation noise than by a description in the digital domain, particularly if that description relies on sample rate or bit depth numbers. [2]…
System Noise Questions
Some questions have been posted in on-line comments and elsewhere:
a) MQA made the unprecedented step of displaying the signal-to-noise (S/N) ratio of all of the charts and graphs not in "dBFS" (dB below Full Scale), but instead by presenting all of their data in "noise per-root Hz dBFS". An example of this was in the original AES Journal article [2]. In this paper, Figure 8 shows that 16 bits of data yields a –144dB noise floor and that 24 bits of data yields a –192dB noise floor. I personally am unaware of any scholarly article concerning digital audio…
Tutorial: Understanding Noise And Signal Plots
The sounds we hear are rarely one thing, in fact sounds convey meaning by changing and combine tonal and atonal elements. Nevertheless engineers will spend a lot of effort using tones (single notes) to investigate frequency response and non-linearity. Similarly we measure noise to try to understand how much there is. In our world background noise is an irremovable feature. A recording system adds noise as do distribution and replay systems. If we are to design or specify or compare, we need a framework within which to be able to estimate…
Tutorial: Temporal Errors In Audio
In our Hierarchical paper [2] section 2.3 Temporal Limits, we explain:
"For the audio distribution channel we can consider temporal resolution in two aspects: its ability to maintain separation between closely spaced events (and not blur them together) and its ability to maintain a precise unquantized time-base within and between channels. Low-pass filtering may ultimately impact the separation of nearby events ... while filters in the digitizing process, that are sharper in the frequency domain, may also bring uncertainty to the start, stop…
Temporal Blur In Sampled Systems
If we look back at the roots of sampled coding systems we encounter Shannon's elegant reconstruction theorem and Nyquist's theorem on channel capacity.[23][24]
A sampled signal can be unambiguously reconstructed if it contains no frequencies higher then Fs/2; it is completely determined by capturing its values at a series of points T = 1/Fs seconds apart and can be reconstructed with a perfect low-pass filter at Fs/2.
There are a number of problems with this conceptual framework for the human listener. First, strictly mathematical, a…
Some Real-World Comparisons
Figure 7: Impulse response of a typical CD channel showing the dispersion in time over ±4ms.
Figure 8: End-to-end impulse magnitude response of MQA compared to typical 192kHz and 48kHz systems and Air at STP and 30% RH. Compared to typical 192kHz sampling, temporal blur of the example is lowered by an order of magnitude. Note the expanded timescale and that only part of the 48kHz response is shown (it extends ±4ms).
Figure 7 shows the end-to-end impulse response for a typical CD channel operating at 44.1kHz. In Figure 8 we see…
Informative Topic: Spectral Content Of Music
Figure 14. Peak spectral level gathered over a corpus of 96kHz and 192kHz recordings.
There is significant content above 20kHz in many types of music, as an analysis of high-rate recordings summarized in Figure 14 has revealed. One notable and common characteristic of musical instrument spectra is that the power declines, often significantly, with rising frequency.
Even though some musical instruments produce sounds above 20kHz [27] it does not necessarily follow that a transparent system needs to reproduce them;…
Understanding Information Diagrams
Figure 18: Shannon diagram showing the capacity of digital channels (area is equivalent to data rate).
Figure 18 compares the coding space for a number of common transmission formats, including CD, and 96 and 192kHz at 24- and 32-bit depths; also shown is the noise-floor for DSD64.
To accommodate the coding capacity of 32-bit LPCM, the vertical scale of this graph is formidable. At the top, 120dB SPL is the threshold of pain; 0dB (the quietest we can perceive) is in the center. The noise-floor of the 32-bit channel is 120dB…
Losslessness Questions
a) Is MQA really lossless?
b) MQA isn't lossless?
c) MQA prevents us changing the signal before playback (eg, room correction or upsampling).
Answers: a & b) This question often seems to assume that lossless is always best but in fact all "lossless" does is to take some bits and to reproduce those same bits at another time or place. It that's all you wanted to do, FLAC would be fine and there would be no need for MQA. The team behind MQA understand not only lossless compression but also lossless processing and data burying. [3…