[Paper 리뷰] Direct Design of Biquad Filter Cascades with Deep Learning by Sampling Random Polynomials
Direct Design of Biquad Filter Cascades with Deep Learning by Sampling Random Polynomials Arbitrary magnitude response와 match 하도록 Infinite Impulse Response filter를 설계하는 것은 어려움 - Yule-Walker method는 효율적이지만 high-order response를 정확하게 match 하지 못함 - Iterative optimization은 우수한 성능을 보이지만 initial condition에 민감 IIRNet 수백만개의 random filter에 대해 학습된 neural network를 사용하여 target magnitude response에서 filter coe..
[Paper 리뷰] Lightweight and Interpretable Neural Modeling of an Audio Distortion Effect Using Hyperconditioned Differentiable Biquads
Lightweight and Interpretable Neural Modeling of an Audio Distortion Effect Using Hyperconditioned Differentiable Biquads Audio distortion effect를 모델링하기 위해 differentiable cacaded biquads를 사용할 수 있음 Hyperconditioned Differentiable Biquads Trainable Infinite Impulse Response (IIR) filter를 hyperconditioned case로 확장 Transformation은 distortion effect의 external parameter를 internal filter와 gain paramete..
[Paper 리뷰] Sinusoidal Frequency Estimation by Gradient Descent
Sinusoidal Frequency Estimation by Gradient Descent Gradient descent를 사용하여 sinusoidal frequency parameter를 추정하는 것은 어려움 - Error function이 non-convex 하고 local minima에 densely populated 되어 있기 때문 Sinusoidal Frequency Estimation by Gradient Descent Complex exponential surrogate의 Wirtinger derivative와 first order gradient-based optimizer를 활용 Differentiable signal processing을 oscillatory component의 fre..
[Paper 리뷰] Differentiable Signal Processing with Black-Box Audio Effects
Differentiable Signal Processing with Black-Box Audio Effects Audio effect를 deep neural network로 통합하여 automate audio signal processing을 수행할 수 있음 DeepAFx Non-differentiable black-box effect layer를 학습시키기 위해 stochastic gradient approximation을 활용하여 end-to-end backpropagation을 생성 Tube amplifier emulation, automatic mastering, breath removal에 대한 audio production 작업에 적용 가능 논문 (ICASSP 2021) : Paper Link..