Loud-signal masking of weak signals enables bit-saving adaptive quantizers

Evidence

Real signals often spend most of their time at low signal levels, but one has to design the quantizer to handle the maximum signal level, even if it isn’t used very often. This means that more bits are used than is strictly necessary most of the time. One way of reducing the number of bits needed to quantize an audio signal is to make the quantizer adapt to the level of the signal because loud signals mask weaker signals, as discussed in Chapter 5. This type of quantizer is known as an “adaptive quantizer,” and can save some bits. — David Howard, Jamie Angus, coustics and Psychoacoustics, 2657

Categorization

• DEFINE: Defines adaptive quantizers and grounds their rationale in psychoacoustic masking.
• XREF: Connects to the masking discussion referenced from Chapter 5 and to the reader’s broader interest in how loud sounds hide weak ones. — connects to: Shaping quantization noise to sit 13 dB below the signal renders it inaudible; Non-uniform quantizer spacing exploits masking and signal statistics to cut noise; Audio compression exploits masking to discard inaudible signal parts — Professor Dr.-Ing. Hugo Fastl, Professor Dr.-Ing. Eberhard, Psychoacoustics- Facts and Models, 2020 (+3 more)
• corroborated: 4 independent passages support this claim — David Howard, Jamie Angus, coustics and Psychoacoustics, 2657

Broader Connections

• Non-uniform quantizer spacing exploits masking and signal statistics to cut noise #expands (0.90)
• Audio compression exploits masking to discard inaudible signal parts #expands (0.85) — Professor Dr.-Ing. Hugo Fastl, Professor Dr.-Ing. Eberhard, Psychoacoustics- Facts and Models, 2020
• Uniform quantization noise requires about 60 dB signal-to-noise to stay masked #qualifies (0.80)
• Perceptual coders exploit masking to cut audio storage and bandwidth #expands (0.80) — David Howard, Jamie Angus, coustics and Psychoacoustics, 1656