no code implementations • 3 Feb 2022 • Johannes Imort, Giorgio Fabbro, Marco A. Martínez Ramírez, Stefan Uhlich, Yuichiro Koyama, Yuki Mitsufuji
Given the recent advances in music source separation and automatic mixing, removing audio effects in music tracks is a meaningful step toward developing an automated remixing system.
no code implementations • 13 Oct 2021 • Bo-Yu Chen, Wei-Han Hsu, Wei-Hsiang Liao, Marco A. Martínez Ramírez, Yuki Mitsufuji, Yi-Hsuan Yang
A central task of a Disc Jockey (DJ) is to create a mixset of mu-sic with seamless transitions between adjacent tracks.
2 code implementations • 11 May 2021 • Marco A. Martínez Ramírez, Oliver Wang, Paris Smaragdis, Nicholas J. Bryan
We present a data-driven approach to automate audio signal processing by incorporating stateful third-party, audio effects as layers within a deep neural network.
1 code implementation • 28 Apr 2021 • Woosung Choi, Minseok Kim, Marco A. Martínez Ramírez, Jaehwa Chung, Soonyoung Jung
This paper proposes a neural network that performs audio transformations to user-specified sources (e. g., vocals) of a given audio track according to a given description while preserving other sources not mentioned in the description.
1 code implementation • 22 Oct 2019 • Marco A. Martínez Ramírez, Emmanouil Benetos, Joshua D. Reiss
Plate and spring reverberators are electromechanical systems first used and researched as means to substitute real room reverberation.
no code implementations • 15 May 2019 • Marco A. Martínez Ramírez, Emmanouil Benetos, Joshua D. Reiss
Audio processors whose parameters are modified periodically over time are often referred as time-varying or modulation based audio effects.
1 code implementation • 9 Apr 2019 • Bhusan Chettri, Daniel Stoller, Veronica Morfi, Marco A. Martínez Ramírez, Emmanouil Benetos, Bob L. Sturm
Our ensemble model outperforms all our single models and the baselines from the challenge for both attack types.
Audio and Speech Processing Sound