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Found 18 papers, 12 papers with code
Differentiable All-pole Filters for Time-varying Audio Systems
Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers.
SyncFusion: Multimodal Onset-synchronized Video-to-Audio Foley Synthesis
Sound design involves creatively selecting, recording, and editing sound effects for various media like cinema, video games, and virtual/augmented reality.
Optimization Techniques for a Physical Model of Human Vocalisation
We present a non-supervised approach to optimize and evaluate the synthesis of non-speech audio effects from a speech production model.
Modulation Extraction for LFO-driven Audio Effects
Low frequency oscillator (LFO) driven audio effects such as phaser, flanger, and chorus, modify an input signal using time-varying filters and delays, resulting in characteristic sweeping or widening effects.
Modelling black-box audio effects with time-varying feature modulation
Deep learning approaches for black-box modelling of audio effects have shown promise, however, the majority of existing work focuses on nonlinear effects with behaviour on relatively short time-scales, such as guitar amplifiers and distortion.
Steerable discovery of neural audio effects
Applications of deep learning for audio effects often focus on modeling analog effects or learning to control effects to emulate a trained audio engineer.
Neural Synthesis of Footsteps Sound Effects with Generative Adversarial Networks
Footsteps are among the most ubiquitous sound effects in multimedia applications.
Direct design of biquad filter cascades with deep learning by sampling random polynomials
In this work, we address some of these limitations by learning a direct mapping from the target magnitude response to the filter coefficient space with a neural network trained on millions of random filters.
WaveBeat: End-to-end beat and downbeat tracking in the time domain
In this work, we propose WaveBeat, an end-to-end approach for joint beat and downbeat tracking operating directly on waveforms.
Efficient neural networks for real-time modeling of analog dynamic range compression
Deep learning approaches have demonstrated success in modeling analog audio effects.
Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks
Despite the popularity of guitar effects, there is very little existing research on classification and parameter estimation of specific plugins or effect units from guitar recordings.
Randomized Overdrive Neural Networks
By processing audio signals in the time-domain with randomly weighted temporal convolutional networks (TCNs), we uncover a wide range of novel, yet controllable overdrive effects.
Modeling plate and spring reverberation using a DSP-informed deep neural network
Plate and spring reverberators are electromechanical systems first used and researched as means to substitute real room reverberation.
A general-purpose deep learning approach to model time-varying audio effects
Audio processors whose parameters are modified periodically over time are often referred as time-varying or modulation based audio effects.
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis.
Unifying Probabilistic Models for Time-Frequency Analysis
In audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts.
Modeling of nonlinear audio effects with end-to-end deep neural networks
In the context of music production, distortion effects are mainly used for aesthetic reasons and are usually applied to electric musical instruments.
A Generative Model for Natural Sounds Based on Latent Force Modelling
Recent advances in analysis of subband amplitude envelopes of natural sounds have resulted in convincing synthesis, showing subband amplitudes to be a crucial component of perception.
