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Context Review Dynamic PD FBAM Conclusions Sound synthesis with Periodically Linear Time Varying Filters Antonio Goulart, Marcelo Queiroz Joseph Timoney, Victor Lazzarini Computer Music Research Group - IME/USP - Brazil Sound and Digital


  1. Context Review Dynamic PD FBAM Conclusions Sound synthesis with Periodically Linear Time Varying Filters Antonio Goulart, Marcelo Queiroz Joseph Timoney, Victor Lazzarini Computer Music Research Group - IME/USP - Brazil Sound and Digital Music Technology Group - NUIM - Ireland antonio.goulart@usp.br Linux Audio Conference - 2015/04/10 1 / 25

  2. Context Review Dynamic PD FBAM Conclusions Motivations New synth sounds ⊲ Low computational cost Virtual Analog Oscillators Usage as audio effect 2 / 25

  3. Context Review Dynamic PD FBAM Conclusions Motivations New synth sounds ⊲ Low computational cost Virtual Analog Oscillators Usage as audio effect The challenge: ⊲ “When I first got some - I won’t call it music - sounds out of a computer in 1957, they were pretty horrible. (...) Almost all the sequence of samples - the sounds that you produce with a digital process - are either uninteresting, or disagreeable, or downright painful and dangerous. It’s very hard to find beautiful timbres. ” Max Mathews, 2010. 3 / 25

  4. Context Review Dynamic PD FBAM Conclusions Contribution LTV theory approach to distortion techniques h ( p , n ) H ( z , n ) H ( ω, n ) 4 / 25

  5. Context Review Dynamic PD FBAM Conclusions Phase Distortion Phaseshaping - US patent 4658691 Casio - CZ Add a phase distortion function to the regular phase generator Sawtooth: Inflection point on the regular (dashed) index � 0 . 5 t 0 ≤ t ≤ d d , t + g ( t ) = 0 . 5 t − d 1 − d + 0 . 5 , d < t < 1 For d = 0 . 05 5 / 25

  6. Context Review Dynamic PD FBAM Conclusions The allpass filter H ( z ) = − a + z − 1 1 − az − 1 Flat magnitude response Frequency dependent phase shift � − a sin ( ω ) � φ ( ω ) = − ω + 2 tan − 1 1 − a cos ( ω ) Reverb, chorus, flanger, phaser, spectral delay 6 / 25

  7. Context Review Dynamic PD FBAM Conclusions Amplitude modulation cos (2 π f c n ) cos (2 π f m n ) = 1 2 cos (2 π f c n + 2 π f m n )+1 2 cos (2 π f c n − 2 π f m n ) 7 / 25

  8. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation Jussi Pekonen, 2008 Coefficient-modulated first-order allpass filter as distortion effect Suggests the method for sound synthesis and audio effects Recall that classic PD is restricted to cyclic tables Derives stability condition | m ( n ) | ≤ 1 ∀ n Recommends appropriate values for m ( n ) Allpass Dispersion on low frequencies φ DC ( n ) = 1 − m ( n ) 1 + m ( n ) 8 / 25

  9. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki, 2009 Spectrally rich phase distortion sound synthesis using allpass filter Time-varying allpass transfer function H ( z , n ) = − m ( n ) + z − 1 1 − m ( n ) z − 1 Phase distortion � − m ( n ) sin ( ω ) � φ ( ω, n ) = − ω + 2 tan − 1 1 − m ( n ) cos ( ω ) 9 / 25

  10. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki � − m ( n ) sin ( ω ) � φ ( ω, n ) = − ω + 2 tan − 1 1 − m ( n ) cos ( ω ) Knowing φ ( ω, n ), use tan ( x ) ≈ x , − ( φ ( ω, n ) + ω ) m ( n ) = 2 sin ( ω ) − ( φ ( ω, n ) + ω ) cos ( ω ) 10 / 25

  11. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki Emulate the classic phase distortion technique � 0 . 5 t 0 ≤ t ≤ d d , t + g ( t ) = 0 . 5 t − d 1 − d + 0 . 5 , d < t < 1 Subtract linear phase from the phase distortion function � ( 1 2 − d ) t d , 0 ≤ t ≤ d g ( t ) = ( 1 2 − d ) 1 − t 1 − d + 0 . 5 , d < t < 1 11 / 25

  12. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki Range for the allpass modulation should be [ − ω, − π ] φ ( ω, t ) = g ( t )((1 − 2 d ) π − ω ) − (1 − 2 d ) π − ω (1 − 2 d ) π Get the modulation function − ( φ ( ω, n ) + ω ) m ( n ) = 2 sin ( ω ) − ( φ ( ω, n ) + ω ) cos ( ω ) Implementation with difference equations y ( n ) = x ( n − 1) − m ( n )( x ( n ) − y ( n − 1)) ⊲ 12 / 25

  13. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki Phase distortion and coefficient modulation functions 13 / 25

  14. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki Outputs with classic PD (solid) and modulated allpass (dashed) 14 / 25

  15. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation J.Timoney, V.Lazzarini, J.Pekonen, V.Valimaki Classic PD and Modulated allpass spectra 15 / 25

  16. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation Arbitrary distortion function 2 f 0 − π � � y ( n ) = 0 . 4 cos ( f 0 ) + 0 . 4 cos + 3 � � 3 f 0 + π 4 f 0 + 4 π � � 0 . 35 cos + 0 . 3 cos 7 3 Shift it to the appropriate range y s ( n ) = − π ( y ( n ) + 1) 2 2 Create your own (: ⊲ 16 / 25

  17. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation Arbitrary distortion function Phase distortion and derived modulation functions 17 / 25

  18. Context Review Dynamic PD FBAM Conclusions Allpass filters coefficient modulation Arbitrary distortion function Waveform and spectrum 18 / 25

  19. Context Review Dynamic PD FBAM Conclusions J.Kleimola, V.Lazzarini, J.Timoney, V.Valimaki, 2009 FeedBack Amplitude Modulation (FBAM) Revisiting of an old idea by A.Layzer tested by Risset in the catalogue ⊲ Modulate oscillator amplitude using its output y ( n ) = cos ( ω 0 n )[1 + β y ( n − 1)] with ω 0 = 2 π f 0 and y [0] = 0 19 / 25

  20. Context Review Dynamic PD FBAM Conclusions FeedBack Amplitude Modulation y ( n ) = cos( ω 0 n )[1 + y ( n − 1)] y ( n ) = cos( ω 0 n ) + cos( ω 0 n ) cos( ω 0 [ n − 1]) + cos( ω 0 n ) cos( ω 0 [ n − 1]) cos( ω 0 [ n − 2]) + ... � k cos 2 ( p ) = 1 = � ∞ m =0 cos[ ω 0 ( n − m )] 2 (1 + cos(2 p )) k =0 cos 3 ( p ) = 1 4 (3 cos( p ) + cos (3 p )) 20 / 25

  21. Context Review Dynamic PD FBAM Conclusions FeedBack Amplitude Modulation LPTV interpretation y ( n ) = x ( n ) + β a ( n ) y ( n − 1) x ( n ) = a ( n ) = cos ( ω 0 n ) in this case (but could be � =) 1 pole coefficient modulated IIR → Dynamic PD ⊲ 21 / 25

  22. Context Review Dynamic PD FBAM Conclusions Feedback Amplitude Modulation β similar to FM’s modulation index 22 / 25

  23. Context Review Dynamic PD FBAM Conclusions Feedback Amplitude Modulation Stability condition � N � � � � cos ( ω 0 m ) � < 1 � β � � � � m =1 Aliasing before instability 23 / 25

  24. Context Review Dynamic PD FBAM Conclusions 2nd order FBAM Two previous outputs with individual β s y ( n ) = cos ( ω 0 n )[1 + β 1 y ( n − 1) + β 2 y ( n − 2)] Narrower pulse and wider band ⊲ 24 / 25

  25. Context Review Dynamic PD FBAM Conclusions Conclusions Reissue of a classic technique Different kind of implementation Input and modulation can be arbitrary signals Deeper investigation of LTV Studying 2nd and higher order systems stability Thanks a lot! antonio.goulart@usp.br 25 / 25

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