Audio symbols with high probability carry less information and need fewer bits

Evidence

In order to implement entropy coding, we have to more closely match the number of bits we use for each symbol to the amount of information it carries. Furthermore, each code word associated with the symbol must have an integer number of bits. The net result of this is that instead of using a fixed number of bits for each symbol, we need to use a number of bits that is related to the information carried by that symbol. For example, we know that in a real audio signal, the signal spends much more time at low amplitudes than high amplitudes, so low amplitudes carry less information and should be encoded with fewer bits than high signal levels. — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 2635

Categorization

• XREF: Connects to Shannon’s information theory and the redundancy of natural audio signals — fits the reader’s broader psychoacoustics purpose and past reading on the soundscape.