Temporal Processing Flashcards
What is the temporal processing limit for human percept?
-Limits for human percept: 1-3 ms
Why is measuring temporal resolution a difficult problem?
-Duration/BW tradeoff
- Solutions:
1) Gaps in broadband noise
2) Time-reversed broadband signals
3) Temporal modulation transfer functions (TMTFs)
How do measure TMTFs?
- Measure if the listener can detect which complex stimulus has a “modulation” in the amplitude
- Measure the “m” (modulation index, depth) at which a person can detect the modulation (20*log[m])
How do you plot TMTFs?
- Y axis: threshold of the amount of modulation required for detection (20*log[m])
- X axis: modulation frequency (Hz)
What do TMTFs show?
- Sensitivity to modulation is better at lower modulation frequencies
- Most important modulations: speech
- Most prominent modulation frequency in speech spectrum: 8 Hz
What does gap detection in noise depend on?
- BW
- CF
Describe gap detection in broadband vs. narrowband noise.
- Broader noise BW with an auditory filter with high CF
- Gap detection improves in broader noise BW because they result in faster fluctuations once passed through an auditory filter
- Faster fluctuations with lower dips make the gap in noise easier to detect than when there are slower fluctuations with higher dips
- Broader BW also results in less ringing which makes the gap easier to detect
- Therefore, broader BW and higher CF results in better temporal resolution
Describe Eddins et al. (1992).
- Measured gap thresholds for noise bands as a function of BW
- Fixed upper cutoff frequency (UCF) but varied BW
- Gap thresholds improved with increased BW but were basically independent of UCF
Why is the single filter hypothesis wrong?
- In Eddins et al. (1992), thresholds did not improve with increased upper cutoff frequency (UCF)
- Used across-frequency comparison (why thresholds improved with increased BW)
Describe gap detection for tones of different phases.
- Standard-phase condition: same non-monotonicities as in Shailer & Moore (1987); when gap duration is an integer multiple of the signal period, the standard-phase condition is identical to the preserved-phase condition
- Reverse-phase condition: mirror image of standard-phase condition (still has non-monotonicities)
- Preserved-phase condition: performance monotonically improved with increased gap duration
How did Shailer & Moore (1987) explain the non-monotonicities in gap detection for standard phase?
- Ringing in the auditory filter
- When the sinusoid is turned off at the start of the gap, the filter continues to respond
- When the gap duration is the period of the sinusoid, the sinusoid following the gap has the same phase as the ringing response
- With 2 extreme gap durations (short, long), the sinusoid following the gap is out of phase with the ringing response
How does hearing loss affect gap detection for tones?
- TMTFs have same shape but occur at higher CBWs and at higher thresholds than for NH
- HL would be expected to have better performance (broader filters, less ringing, better performance than NH)
- Less non-monotonicities than with NH subjects
- Performance improves faster
Describe expected gap detection in CI users.
- CI patients have total hearing loss, so any deficits in temporal mechanisms caused by cochlear damage should be maximized
- If HL causes retrocochlear deterioration of temporal resolution, we would expect CI patients (like HI) to have poor gap thresholds
- However, if gap detection were limited by cochlear processing, CI patients might have smaller gap thresholds than NH listeners because their nerves are stimulated directly with no mechanical resonance to limit the process
- Might expect better gap detection than NH because no ringing/smearing
What are the effects of level on gap detection for CI users?
- Gap detection improves with increased level until a certain level at which threshold saturates
- Although there is variability, trend is monotonic
Describe the sliding temporal integration window.
- A temporal window is a weighing function applied to the instantaneous energy of the signal over the time period covered by the window
- The window slides in time, so its output as a function of time represents a running weighed average of the energy of the signal (temporal excitation pattern)