Methods for Modeling Realistic Methods for Modeling Realistic - - PowerPoint PPT Presentation

▶
methods for modeling realistic methods for modeling
SMART_READER_LITE
LIVE PREVIEW

Methods for Modeling Realistic Methods for Modeling Realistic - - PowerPoint PPT Presentation

Dec 15, 2023 252 likes •469 views

DAFX00, Verona, Italy, December 2000 HELSINKI UNIVERSITY OF TECHNOLOGY Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String Synthesis: Playing in Plucked-String Synthesis: Analysis, Control and Synthesis

slide-1
SLIDE 1

Laurson, Erkut & Välimäki 2000 1

HELSINKI UNIVERSITY OF TECHNOLOGY

Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String Synthesis: Playing in Plucked-String Synthesis: Analysis, Control and Synthesis Analysis, Control and Synthesis

Mikael Laurson1, Cumhur Erkut2, and Vesa Välimäki2

1Center for Music and Technology, Sibelius Academy

(Helsinki, Finland)

2Laboratory of Acoustics and Audio Signal Processing,

Helsinki University of Technology (Espoo, Finland)

DAFX’00, Verona, Italy, December 2000

slide-2
SLIDE 2

Laurson, Erkut & Välimäki 2000 2

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 1. Introduction
  • 2. Structure of the Synthesizer
  • 3. Analysis of Recorded Tones & Resynthesis
  • Dynamics and pizzicato
  • 4. Control
  • 5. Synthesis Using PWSynth
  • 6. Conclusions and Future Plans

Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String Synthesis: Playing in Plucked-String Synthesis: Analysis, Control and Synthesis Analysis, Control and Synthesis

slide-3
SLIDE 3

Laurson, Erkut & Välimäki 2000 3

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 1. Introduction
  • 1. Introduction
  • Physical modeling has been an active research field

for the past decade

  • Most popular approach based on digital waveguides

– – Commuted Waveguide Synthesis Commuted Waveguide Synthesis (Smith, 1993; Karjalainen et al., 1993)

  • Our current guitar synthesizer

– Implemented using PWSynth and ENP – Based on analysis of recorded guitar tones – – Sound example: Prelude by J. S. Bach Sound example: Prelude by J. S. Bach

slide-4
SLIDE 4

Laurson, Erkut & Välimäki 2000 4

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 2. Structure of the Synthesizer
  • 2. Structure of the Synthesizer
  • Basic string model

(Jaffe & Smith, 1983; Välimäki et al. 1996)

) (n x ) 3 ( h ) (n y )] ( 1 )[ ( n a n g + ) (n a

1 −

z

1 −

z

1 −

z

1 −

z ) 2 ( h ) 1 ( h ) ( h

+

  • M

z− ) (

1 n

y ) (n y

d L+

Loop filter

FIR fractional delay filter FIR fractional delay filter Loop filter Loop filter Delay line Delay line

slide-5
SLIDE 5

Laurson, Erkut & Välimäki 2000 5

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 2. Structure of the Synthesizer
  • 2. Structure of the Synthesizer (2)

(2)

  • Commuted waveguide synthesis (sampling + modeling)
  • Excitations & special effects stored in a database

P lucking- point filter Tim bre control D atabase of excitation signals From sym pathetic coupling m atrix To sym pathetic coupling m atrix O ut

) (

h z

S ) (

v z

S

Special effects

slide-6
SLIDE 6

Laurson, Erkut & Välimäki 2000 6

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Analysis of Recorded Tones
  • 3. Analysis of Recorded Tones
  • Anechoic recordings

Anechoic recordings of guitar playing

  • Signal analysis using short-time Fourier transform

short-time Fourier transform (Välimäki et al. 1996)

  • Parameter estimation

Parameter estimation using iterative methods (Erkut et al., AES Conv., Feb. 2000)

  • Excitation signals

Excitation signals obtained by subtracting the harmonics from recorded tones, and equalization (Tolonen 1998; Välimäki & Tolonen, JAES 1998)

slide-7
SLIDE 7

Laurson, Erkut & Välimäki 2000 7

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Modeling Dynamics
  • 3. Modeling Dynamics
  • Use the Timbre filter

Timbre filter to model dynamics – 2nd-order IIR filter instead of a one-pole filter – Change coefficients according to dynamic level

  • Store filter parameters

Store filter parameters instead of excitation signals (i.e., save memory)

  • Enables interpolation of dynamic levels between the

analyzed cases (forte, piano, pianissimo etc.)

  • Changing dynamics by scaling &

scaling & lowpass lowpass/ /highpass highpass filtering filtering the excitation signal (Erkut et al. 2000)

slide-8
SLIDE 8

Laurson, Erkut & Välimäki 2000 8

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Modeling Dynamics
  • 3. Modeling Dynamics (2)

(2)

  • Differences in the

spectra at various dynamic levels – Overall level – Spectral tilt

  • Spectral

Spectral envelope fit envelope fit using LPC using LPC (red line) (red line)

slide-9
SLIDE 9

Laurson, Erkut & Välimäki 2000 9

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Modeling Dynamics
  • 3. Modeling Dynamics (3)

(3)

  • Divide the 2nd-order transfer functions
  • Filter H(z) is used as the Timbre filter

2 2 1 1

1 ) (

− − +

+ = z a z a g z A

a 2 2 1 1

1 ) (

− − +

+ = z b z b g z B

b 2 2 1 1 2 2 1 1

1 ) 1 )( / ( ) ( ) ( ) (

− − − −

+ + + + = = z a z a z b z b g g z B z A z H

b a

→ and

slide-10
SLIDE 10

Laurson, Erkut & Välimäki 2000 10

HELSINKI UNIVERSITY OF TECHNOLOGY

Sound Examples: Dynamic Levels Sound Examples: Dynamic Levels

  • Now we can synthesize different dynamic levels using
  • ne excitation signal
  • ne excitation signal but different Timbre filter

different Timbre filter

  • Comparison of synthetic tones

1. Fortissimo Fortissimo (without Timbre filter) (without Timbre filter) 2. Forte Forte (without Timbre filter) (without Timbre filter) 3. Forte Forte (with fortissimo excitation & Timbre filter) (with fortissimo excitation & Timbre filter) Playlist = { 1 2 3 pause 1 2 3 pause 2 3 }

slide-11
SLIDE 11

Laurson, Erkut & Välimäki 2000 11

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Pizzicato Tones
  • 3. Pizzicato Tones
  • Pizzicato = pluck the string & lightly damp the string

with the palm of the hand

  • Pizzicato tones

Pizzicato tones decay fast ! decay fast !

slide-12
SLIDE 12

Laurson, Erkut & Välimäki 2000 12

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 3. Pizzicato Tones
  • 3. Pizzicato Tones (2)

(2)

  • How to synthesize pizzicato tones efficiently

– Change the Loop filter & Timbre filter

  • Timbre filter obtained just

like above (2nd-order LPC fit and divide transfer functions)

slide-13
SLIDE 13

Laurson, Erkut & Välimäki 2000 13

HELSINKI UNIVERSITY OF TECHNOLOGY

Pizzicato Sound Examples Pizzicato Sound Examples

  • Comparison of synthetic tones

1. Normal pluck Normal pluck (without Timbre filter) (without Timbre filter) 2. Pizzicato Pizzicato (without Timbre filter) (without Timbre filter) 3. Pizzicato Pizzicato (Normal pluck excitation & Timbre filter) (Normal pluck excitation & Timbre filter) Playlist = { 1 2 3 pause 1 2 3 pause 2 3 }

slide-14
SLIDE 14

Laurson, Erkut & Välimäki 2000 14

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 4. Control
  • 4. Control
  • Control with the help of ENP

ENP (Expressive Notation Package) – Lisp Lisp-based package in PatchWork PatchWork – Supports standard & non-standard expressions (Laurson et al., ICMC’99; Kuuskankare & Laurson, JIM’2000)

  • User can define a score & add expression info
slide-15
SLIDE 15

Laurson, Erkut & Välimäki 2000 15

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 4. Control
  • 4. Control (2)

(2)

  • Example from the classical guitar repertoire
  • Sound example:

Sound example: Madroños Madroños by F. M. by F. M. Torroba Torroba

slide-16
SLIDE 16

Laurson, Erkut & Välimäki 2000 16

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 4. Control
  • 4. Control (3)

(3)

  • Example of non-standard, modern notational

conventions: special noteheads trigger samples

  • Sound example:

Sound example: Lettera Amorosa Lettera Amorosa by J. A. Muro by J. A. Muro – – Includes special effects, such as sampled knocks & Includes special effects, such as sampled knocks & rubbing of strings rubbing of strings

slide-17
SLIDE 17

Laurson, Erkut & Välimäki 2000 17

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 5. Synthesis Using PWSynth
  • 5. Synthesis Using PWSynth
  • Graphical programming environment for sound

synthesis within PatchWork

slide-18
SLIDE 18

Laurson, Erkut & Välimäki 2000 18

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 5. Synthesis Using PWSynth
  • 5. Synthesis Using PWSynth (2)

(2)

  • Parameters stored in matrices

matrices (see below)

  • Every parameter has a pathname

pathname, such as guitar1/2/lfcoef which points to the loop filter coefficient of the 2nd string of Guitar #1 – Like in OSC (Wright & Freed, 1997)

slide-19
SLIDE 19

Laurson, Erkut & Välimäki 2000 19

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 6. Conclusions
  • 6. Conclusions
  • Newest developments in model-based guitar synthesis
  • Commuted waveguide synthesis

Commuted waveguide synthesis combines modeling & sampling – Strings modeled with digital waveguides – Excitations & effects extracted from recordings

  • Methods were proposed for synthesizing various

various dynamic levels dynamic levels and pizzicato tones pizzicato tones

  • Sound examples available at our Web site:

http://www.acoustics.hut.fi/demo/dafx2000-synth/

slide-20
SLIDE 20

Laurson, Erkut & Välimäki 2000 20

HELSINKI UNIVERSITY OF TECHNOLOGY

  • 6. Future Research
  • 6. Future Research
  • Reduce redundancy between excitation signals

– Model low-frequency body modes with digital resonators, as suggested earlier (Välimäki et al., 1996; Tolonen, 1998)

  • Reduce the size of the excitation database
  • Improved parametrization of excitation signals