Instrument filtering adds predictability that audio coders exploit as redundancy.
Evidence
In Chapter 4 we saw that all musical instruments, including the human voice, could be modeled as a sound source followed by sound modifiers, which apply a filtering function. In the limit the source may be regular spaced impulses, for pitched instruments, a single pulse for percussion instruments, random noise for fricatives, or a combination of them all. A filter that combines the effect of the source with the acoustic effect of the instrument and output to shape the final sound then follows this. The effect of this filtering is to add correlation to the audio signal. Correlation implies that information from previous samples is carried over to the current sample, as shown in Figure 7.34. The basic principle behind redundancy — David Howard, Jamie Angus, coustics and Psychoacoustics, 2592
Categorization
Category: Causal Relationships
- XREF: Builds directly on the source-filter model of Chapter 4, showing its coding payoff.
Related
- Efficient audio coding discards predictable signal components and encodes only novelty (similarity 0.83)
- Lossless audio coding works by predicting and stripping signal correlations (similarity 0.80)
- All musical instruments and voices share a source-filter acoustic structure (similarity 0.79)
- Redundancy removal effectiveness trades off against the resources needed to encode side information (similarity 0.78)
Broader Connections
- Instrument frequency ranges leave room for inaudible filtering
#corroborates(0.85) — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 2408 - Audio compression maximizes information by encoding only unpredictable signal parts
#corroborates(0.80) — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 2602 - Lossless audio coding works by predicting and stripping signal correlations
#expands(0.75) — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 2605