Joshua D. Reiss | DeepAI

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∙ 08/30/2023

General Purpose Audio Effect Removal

Although the design and application of audio effects is well understood,...

0 Matthew Rice, et al. ∙

∙ 07/10/2023

Vocal Tract Area Estimation by Gradient Descent

Articulatory features can provide interpretable and flexible controls fo...

0 David Südholt, et al. ∙

∙ 05/22/2023

Modulation Extraction for LFO-driven Audio Effects

Low frequency oscillator (LFO) driven audio effects such as phaser, flan...

0 Christopher Mitcheltree, et al. ∙

∙ 07/18/2022

Style Transfer of Audio Effects with Differentiable Signal Processing

We present a framework that can impose the audio effects and production ...

0 Christian J. Steinmetz, et al. ∙

∙ 12/06/2021

Steerable discovery of neural audio effects

Applications of deep learning for audio effects often focus on modeling ...

0 Christian J. Steinmetz, et al. ∙

∙ 10/07/2021

Direct design of biquad filter cascades with deep learning by sampling random polynomials

Designing infinite impulse response filters to match an arbitrary magnit...

0 Joseph T Colonel, et al. ∙

∙ 10/04/2021

WaveBeat: End-to-end beat and downbeat tracking in the time domain

Deep learning approaches for beat and downbeat tracking have brought adv...

0 Christian J. Steinmetz, et al. ∙

∙ 02/11/2021

Efficient Neural Networks for Real-time Analog Audio Effect Modeling

Deep learning approaches have demonstrated success in the task of modeli...

0 Christian J. Steinmetz, et al. ∙

∙ 12/06/2020

Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks

Despite the popularity of guitar effects, there is very little existing ...

0 Marco Comunità, et al. ∙

∙ 10/08/2020

Randomized Overdrive Neural Networks

By processing audio signals in the time-domain with randomly weighted te...

0 Christian J. Steinmetz, et al. ∙

∙ 10/22/2019

Modeling plate and spring reverberation using a DSP-informed deep neural network

Plate and spring reverberators are electromechanical systems first used ...

0 Marco A. Martínez Ramírez, et al. ∙

∙ 05/15/2019

A general-purpose deep learning approach to model time-varying audio effects

Audio processors whose parameters are modified periodically over time ar...

0 Marco A. Martínez Ramírez, et al. ∙

∙ 01/31/2019

End-to-End Probabilistic Inference for Nonstationary Audio Analysis

A typical audio signal processing pipeline includes multiple disjoint an...

0 William J. Wilkinson, et al. ∙

∙ 11/06/2018

Unifying Probabilistic Models for Time-Frequency Analysis

In audio signal processing, probabilistic time-frequency models have man...

0 William J. Wilkinson, et al. ∙

∙ 10/15/2018

Modeling of nonlinear audio effects with end-to-end deep neural networks

In the context of music production, distortion effects are mainly used f...

0 Marco Martínez, et al. ∙

∙ 03/29/2018

An empirical approach to the relationship between emotion and music production quality

In music production, the role of the mix engineer is to take recorded mu...

0 David Ronan, et al. ∙

∙ 03/27/2018

Automatic Minimisation of Masking in Multitrack Audio using Subgroups

The iterative process of masking minimisation when mixing multitrack aud...

0 David Ronan, et al. ∙

∙ 02/02/2018

A Generative Model for Natural Sounds Based on Latent Force Modelling

Recent advances in analysis of subband amplitude envelopes of natural so...

0 William J. Wilkinson, et al. ∙

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