2 citations · 4 across the 7 of their papers we have counts for
7 papers · 1 filter
NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects
Marco Comunità, Christian J. Steinmetz, Joshua D. Reiss
We present NablAFx, an open-source framework developed to support research in differentiable black-box and gray-box modeling of audio effects. Built in PyTorch, NablAFx offers a ve…
Differentiable Black-box and Gray-box Modeling of Nonlinear Audio Effects
Marco Comunità, Christian J. Steinmetz, Joshua D. Reiss
Audio effects are extensively used at every stage of audio and music content creation. The majority of differentiable audio effects modeling approaches fall into the black-box or g…
Exploring trends in audio mixes and masters: Insights from a dataset analysis
Angeliki Mourgela, Elio Quinton, Spyridon Bissas +2
We present an analysis of a dataset of audio metrics and aesthetic considerations about mixes and masters provided by the web platform MixCheck studio. The platform is designed for…
FolAI: Synchronized Foley Sound Generation with Semantic and Temporal Alignment
Riccardo Fosco Gramaccioni, Christian Marinoni, Emilian Postolache +4
Traditional sound design workflows rely on manual alignment of audio events to visual cues, as in Foley sound design, where everyday actions like footsteps or object interactions a…
An automatic mixing speech enhancement system for multi-track audio
Xiaojing Liu, Hongwei Ai, Joshua D. Reiss
We propose a speech enhancement system for multitrack audio. The system will minimize auditory masking while allowing one to hear multiple simultaneous speakers. The system can be…
SyncFusion: Multimodal Onset-synchronized Video-to-Audio Foley Synthesis
Marco Comunità, Riccardo F. Gramaccioni, Emilian Postolache +3
Sound design involves creatively selecting, recording, and editing sound effects for various media like cinema, video games, and virtual/augmented reality. One of the most time-con…
High-Fidelity Noise Reduction with Differentiable Signal Processing
Christian J. Steinmetz, Thomas Walther, Joshua D. Reiss
Noise reduction techniques based on deep learning have demonstrated impressive performance in enhancing the overall quality of recorded speech. While these approaches are highly pe…