Physics and Neurophysiology of Hearing

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Transcription:

Physics and Neurophysiology of Hearing H.G. Dosch, Inst. Theor. Phys. Heidelberg I Signal and Percept II The Physics of the Ear III From the Ear to the Cortex IV Electrophysiology

Part I: Signal and Percept 1)The time scales in hearing 2)Relation between Physics and Sensation (Psychophysics) a) Propagation and Production of Sound b) The principal relations and caveats c) A Byte of Signal processing (mainly Fourier etc) d) Application to acoustics: Ohms Law e) Theory of Musical Consonance f) Fusion of Harmonics and Fundamental Tracking

Sound pressure curve of the sentence: each acoustical signal can be mapped unto a sound pressure curve Typical time scale of variation 0.1 s and larger sound-pressure-example.wav in praat1.collection

selection of the previous sentence: mapped Typical time scale of variation: 10 ms sound-pressure-selection.wav in praat1.collection

101praat: sinfreqmod10.wav sinfreqmod100.wav

Time scales in auditive processes Time scales in visual processes

Original collage by Helmholtz to illustrate the optical and acoustical spectrum. The red has faded away The reception of sound waves in the ear is achieved by mechanical means on the basilar membrane, the reception of light by chemical processes in the retina. In the following only concerned on the time variations in the ms range.

time reolution for angular resolution of 10 degrees 101praat gap01-005.wav in 1praat

2 Relation between Physics and Sensation Signal-Percept Psychophysics Principal perceived properties of sound: Loudeness (volume) Pitch Timbre

2a

1 0.5 2 4 6 8 10 12 14-0.5-1 x x t t

1 0.5 0.5 1 1.5 2 2.5 3-0.5-1 101praat sin440

2b Relation between acoustical signal (sound pressure) and perception (to be refined later) Amplitude of sp Loudeness, Relation Energy-loudeness not so simple 101praat: chain leise-mittel-laut 101praat: karm1,harm3,harm7

Periodicity pitch of the tone 101praat: tief-hoch.wav again: real life is a bit more complicated 101praat: sound-440_3-5, 366_4_6

A2 A1 A a a' a'' a''' a''''

101praat: sound440- sound 13_75c (pitch-range.collection)

Most complicated sensation: timbre not (approximately) 1 dimensional like volume and pitch but many properties: full, thin, soft, harsh... general relation: form of the SP curve timbre A very important distinction is the different timbre of different vowels

The human vocal tract

The vowels sound very different, though the sp curves look similar: 101praat: e_reg - u_reg

The sound pressure curves look different, but the sounds are practically indistinguishable 101prat: schroederplus10, sin10,cos10

Fourier and wavelet transforms Fourier transform: magic formula

Convolution:

power spectrum Signal T 2T 1/T 2/T 3/T fundamental higher harmonics partial tones

Fourier transform

Fourier transform b=0.5 b=2

+ c=0 b=0.5 b=2

db spectral function power spectrum

Windowed Fourier Analysis, Wavelet analysis Fourier analysis over a time window, g(t) : possible time windows rectangular Gaussian window

Representaion windowed Fourier transform by Spectrogramm: time as x-axes, frequency as y axis and intensity as gray value Example: tone with modulated frequency: modulation frequency 3 Hz sin(2*pi*100*x-4*cos(2*pi*3*x)) Spectrogram D=0.05 s 102praat: frequency-modulated.wav Spectrum

Spectrogram and spectrum of ``Each acoustical signal can be mapped onto a sound pressure curve''

Spectrogram and spectrum taken at 2.1 s with gaussian window 0.05 s

h(u) is called a ``note'' : 102praat note.wav

In acoustics the gamma-tone is a particularly popular wavelet signal and spectrum of gamma-tone with t=4 b = 150 Hz =1000 Hz

Vowels, spectra and signals 102praat vokale-hgd rauschen fuer rauschvokale a 1000 1400 e 500 2300 i 320 3200 o 500 1000 u 320 800

App. of Helmholtz to produce artificially vowels sponsored by Ludwig II von Bayern

The sound pressure curves look different, but the sounds are practically indistinguishable but the power spectra are up to a scale identical 102

First refinement: 102praat cymbal.wav, noise.wav Timbre determined by the power spectrum General features: No structure in sp curve and in spectrum : Noise

Few spectral lines (few harmonics) soft tone many harmonics sharp tone 102praat flute.wav spinett.wav i-reg.wav cymbal.wav noise.wav click.wav

Ohm's Law of Acoustics: Ohm 1841, Helmholtz 1863 1) Ear performs a (windowed) Fourier analysis 2) Phases play no role. 3) The different Harmonics of a periodic tone are fused 4) Pitch of a sound determined by lowest harmonic, roughly: long time scales (>0.1 s) processed as temporal properties, short time scales ( < 0.1 s) as power spectral properties

Independence of phases: schroederplus10, sin10

Apparatus of helmholtz to test the independence on phases (Tonempf.)

102praat: sin-coherent.wav sin-random,wav Fourier transform should only differ in phase, i.e. identical power spectrum but: spectra over finite time interval look also different

Our ear performs a windowed Fourier analysis, since we can perceive directly time variations of ca 0.1 s, this should be the maximal width of the window. Example beats and roughness. 102praat beats-third.wav beats-10.wav beats-rough.wav

based on pysiology of the ear Theory of harmony Pythagoras - Helmholtz c(530) 530 1060 1590 2120 2650 3180 3710 4240 9:8 d(590) 590 1180 1770 2360 2950 3540 4130 4720 3:2 g(790) 790 15:8 h(1000) 1000 2000 3000 4000 2:1 c(1060) 1060 2120 3180 4240 live-music 1580 2370 3160 3950

Calculations of Helmholtz for the degree of roughness for a violin

Helmholtz, 1863 dissonanz Kameoka, Kuriyagawa, 1969 consonanz

Interval od roughness larger at low frequencies: fifth minor third fifth minor third Dosch and Specht, 1986 average of 89 subjects

Chopin, Scherzo Beetvoven, Appasionata

But one can also hear the components, some people better, some worse. 102praat sin-1, sin-5,

Fusion of tones A tone with several harmonics: is it a single tone or a collection of tones? both: Helmholtz: we perceive synthetically (perzipieren) the whole tone we can perceive analytically (apperzipieren) the components of the tone. 102praat sin-1.wav sin-5.wav chain-harmonic-insert.wav

The missing fundamental We now take off components from below 102praat chain-fundamental-tracking.collection ca g''' e''' cis''' a'' e'' a' a We take subsequently one harmonic tone out of the complex tone

This happens also in musical instruments 103praat 27_5Hz_A2_real_steinway.wav 110Hz-A_real

103praat 3250Hz-a4-real-steinway

Explanation until ca 1940 : Difference tones For a harmonic tone the difference ton is the fundamental tone

103praat dif-tone-laut, leise 1000,1220 Hz low level high level Spectrogram of the rcorded tone, consisting of two components at 1000 and 1220 Hz. At the high level the nonlinear distortions are clearly visible.

Schouten: The periodicity of the tone is essential for the pitch of the ``residue'', that is the perceived, but not present fundamental tone. Indeed sp curves show this periodicity:

sp for the harmonic tones 1-7, 2-7,3-7, 4-7,5-7,7-7, 7

The difference tone was excluded by van Schouten by a series of ingenious experiments. A particular simple one is the shifted hamonic tone.

The difference tone was excluded by van Schouten by a series of ingenious experiments. A particular simple one is the shifted hamonic tone. 103praat harm-200 200+40 one hears

The difference tone was excluded by van Schouten by a series of ingenious experiments. A particular simple one is the shifted hamonic tone with missing fundamental. one hears 204-harm

The fact that the shifted tone has a ditincly different pitch is a sure sign that the difference tone is not reponsible for fundamental tracking, since the difference tone is unaffected by the shift The question what determines the pitch of a complex tone is still controversial. We shall come back to it after looking closer into the physics of the ear and the auditory pathway.