Download presentation

Presentation is loading. Please wait.

Published byMacy Langdale Modified about 1 year ago

1

2
Pitch of unresolved harmonics: Evidence against autocorrelation Christian Kaernbach and Carsten Bogler Institut für Allgemeine Psychologie, Universität Leipzig Talk presented at “Pitch: Neural Coding and Perception” 4th-18th August, 2002, Hanse-Wissenschaftskolleg, Delmenhorst, Germany IntroductionPitch of unresolved harmonics The ur-modelLicklider, 1951 The argumentKaernbach & Demany, 1998 ConfirmationKaernbach & Bering, 2001 Trying to convincePilot data FailureShort survey on current models G rumble

3
Interlude Fugue G-major by Johann Mattheson from “ Wohlklingende Fingersprache ” performed by Gisela Gumz, Clavichord

4
single note of a clavichord, 518 Hz Pitch of unresolved harmonics SpectrogramExcitation pattern in the cochlea (LUT Ear)

5
simplification: slightly more complex: Processing of temporal structure see Poster by Carsten Bogler

6
Studying temporal processing with clicks simple periodic: complex periodic: aperiodic:

7
Autocorrelation: The ur-model Licklider, 1951 from cochlea delay line fast line coincidence cells Autocorrelation in general s(t) s(t- ) w(t-t 0 ) dt (s(t)) s(t- ): triggered correlation (AIM) s(t) =the stimulus cochlea excitation simulated spike trains + coincidence recorded spike trains + coincidence AC( ,t 0 ) =

8
abx 1st- versus 2nd-order temporal regularity Kaernbach and Demany, 1998 kxx : k = 5ms, x [0,10] ms kkk abx : a [0,10] ms, b = 10 - a, x [0,10] ms a b kxxxkxxxx high-pass filtered, low-pass masked, Fc = 6 kHz x kxx

9
1st- versus 2nd-order temporal regularity Kaernbach and Demany, 1998 target type:kxxkxxxkxxxxabx x [0,10][0,10][0,10][0,10]ms AC peak at55510ms task: discriminate regular sequence from random sequence procedure: adaptive reduction of the length of the sequence abx [0,5] 5

10
abx 1st- versus 2nd-order temporal regularity Kaernbach and Demany, 1998 kxx : k = 5ms, x [0,10] ms kkk abx : a [0,10] ms, b = 10 - a, x [0,10] ms a b kxxxkxxxx high-pass filtered, low-pass masked, Fc = 6 kHz x kxx =

11
Reducing the cut frequency Kaernbach and Bering, 2001 pitch JNDs for periodic click sequences, high-pass filtered, low-pass masked, for 15 subjects confirm Kaernbach & Demany with cut frequency = 2 kHz (x [0,15] ms)

12
Simplifying abx & kxx too complicated. ab = periodic sequence + interfering clicks –Kaernbach & Demany 1998: vary amplitude of interfering clicks –vary cut frequency, compare with jnd (cf. Kaernbach & Bering, 2001) ab with a [0,4], b = 8 - a, versus xy with x [0,4], y [4,8].

13
abx Summary of evidence kxxxkxxxx x kxx = Further evidence: Carlyon, 1996 mixture of two complex tones composed of unresolved harmonics with different F 0 produces no clear-cut pitch percept Plack & White, 2000 pitch shifts due to variations of a gap between two click sequences are incompatible with autocorrelation ab xy

14
Survey on current models JASA online search autocorrelation (abstract type) psychological acoustics revised after 9/1998 applying/advocating autocorrelation Appeal AC modelers: test your models with 2nd-order regularities publish results (positive or negative) eventually: modify your models Appeal AC modelers: test your models with 2nd-order regularities publish results (positive or negative) eventually: modify your models

15
The Pisa effect

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google