The ear’s time-frequency resolution cannot be modeled by fixed-length frames

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 (#contradicts, via linked claim)

Categorization

• XREF: connects to: Human hearing is highly nonlinear and cannot be LTI-modelled beyond peripheral parts; Time and frequency resolution cannot both be improved simultaneously — Toole, Floyd E, Sound reproduction- the acoustics and…, 951; Analysis window length of 10-30 ms is chosen to match auditory time-frequency resolution (+5 more)

Related

• DFT-based windowing explains basic auditory frequency resolution properties (similarity 0.90)
• Time and frequency resolution cannot both be improved simultaneously (similarity 0.89)
• Frequency and time resolution are mutually exclusive trade-offs in any analysis of sound. (similarity 0.87)
• The human hearing system compromises between frequency and time resolution, unlike ideal filters (similarity 0.86)
• Frequency-domain analysis mirrors how the human ear processes sound (similarity 0.86)
• Hearing’s temporal resolution varies from 1-2 ms depending on frequency (similarity 0.86)
• Time–frequency audio processing exploits the ear’s own spectral analysis structure (similarity 0.85)
• The ear’s analysis resembles Fourier frequency decomposition of sound (similarity 0.84)
• Hearing-modeling spectrograms use an ERB frequency axis from modeled auditory filters. (similarity 0.84)
• Human hearing is highly nonlinear and cannot be LTI-modelled beyond peripheral parts (similarity 0.83)
• Hearing waveform beats proves the ear detects time-domain shape (similarity 0.83)
• Normal hearing yields a temporal resolution factor near unity (similarity 0.82)
• The hearing system analyzes complex sounds by linear superposition of component responses (similarity 0.82)
• Only harmonics separated by more than the ear’s critical bandwidth are resolved (similarity 0.82)
• Auditory spectrum computation begins with FFT then emulates hearing sensitivity via filtering and weighting. (similarity 0.81)

Broader Connections

• The human hearing system compromises between frequency and time resolution, unlike ideal filters #expands (0.92)
• Frequency-domain analysis mirrors how the human ear processes sound #contradicts (0.85) — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 377