Apple Soundtrack Pro 2 - Manual (Page 475)

Appendix B Audio Fundamentals 475
When a sample is made, the audio level of the analog signal often falls in the spaces
between rungs. In this case, the sample must be rounded to the nearest rung. The bit
depth of a digital audio sample determines how closely the rungs are spaced. The more
rungs available (or, the less space between rungs), the more precisely the original
signal can be represented.
Quantization errors occur when a digital audio sample does not exactly match the
analog signal strength it is supposed to represent (in other words, the digital audio
sample is slightly higher or lower than the analog signal). Quantization errors are also
called rounding errors because imprecise numbers represent the original analog audio.
For example, suppose an audio signal is exactly 1.15 volts, but the analog-to-digital
converter rounds this to 1 volt because this is the closest bit value available. This
rounding error causes noise in your digital audio signal. While quantization noise may
be imperceptible, it can potentially be exacerbated by further digital processing.
Always try to use the highest bit depth possible to avoid quantization errors.
The diagram on the far right shows the highest bit depth, and therefore the audio
samples more accurately reflect the shape of the original analog audio signal.
For example, a 1-bit system (a ladder with only two rungs) can represent either silence
or full volume, and nothing in between. Any audio sample that falls between these
rungs must be rounded to full volume or silence. Such a system would have absolutely
no subtlety, rounding smooth analog signals to a square-shaped waveform.
Analog waveform Audio sample
Sine Square