DFT-based windowing explains basic auditory frequency resolution properties
Evidence
Representing signals in the frequency domain, as decompositions into their frequency components, is important not only as a powerful signal processing technique but also because it resembles the way the human ear analyses signals. Audio signals that we are able to hear as sounds are thus often analysed by means of frequency transforms in order to find their audible features and cues. — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 377 (
#exemplifies, via linked claim)
Categorization
- XREF: connects to: Analysis window length of 10-30 ms is chosen to match auditory time-frequency resolution; Complex QMF resolution must be supplemented to match auditory frequency selectivity; Frequency-domain analysis mirrors how the human ear processes sound — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 377 (+2 more)
Broader Connections
- The ear’s time-frequency resolution cannot be modeled by fixed-length frames
#complicates(0.82) - Frequency-domain analysis mirrors how the human ear processes sound
#exemplifies(0.80) — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 377 - Complex QMF resolution must be supplemented to match auditory frequency selectivity
#expands(0.78)