63 citations · 117 across the 16 of their papers we have counts for
7 papers · 1 filter
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Cinematic Demixing Track
Stefan Uhlich, Giorgio Fabbro, Masato Hirano +14
This paper summarizes the cinematic demixing (CDX) track of the Sound Demixing Challenge 2023 (SDX'23). We provide a comprehensive summary of the challenge setup, detailing the str…
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai +24
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music so…
Automatic music mixing with deep learning and out-of-domain data
Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Giorgio Fabbro +3
Music mixing traditionally involves recording instruments in the form of clean, individual tracks and blending them into a final mixture using audio effects and expert knowledge (e…
Distortion Audio Effects: Learning How to Recover the Clean Signal
Johannes Imort, Giorgio Fabbro, Marco A. Martínez Ramírez +3
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 syste…
Music Demixing Challenge 2021
Yuki Mitsufuji, Giorgio Fabbro, Stefan Uhlich +6
Music source separation has been intensively studied in the last decade and tremendous progress with the advent of deep learning could be observed. Evaluation campaigns such as MIR…
Training Speech Enhancement Systems with Noisy Speech Datasets
Koichi Saito, Stefan Uhlich, Giorgio Fabbro +1
Recently, deep neural network (DNN)-based speech enhancement (SE) systems have been used with great success. During training, such systems require clean speech data - ideally, in l…
Speech Synthesis and Control Using Differentiable DSP
Giorgio Fabbro, Vladimir Golkov, Thomas Kemp +1
Modern text-to-speech systems are able to produce natural and high-quality speech, but speech contains factors of variation (e.g. pitch, rhythm, loudness, timbre)\ that text alone…