280 citations · 725 across the 9 of their papers we have counts for
9 papers
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…
From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion
Robin San Roman, Yossi Adi, Antoine Deleforge +3
Deep generative models can generate high-fidelity audio conditioned on various types of representations (e.g., mel-spectrograms, Mel-frequency Cepstral Coefficients (MFCC)). Recent…
Simple and Controllable Music Generation
Jade Copet, Felix Kreuk, Itai Gat +5
We tackle the task of conditional music generation. We introduce MusicGen, a single Language Model (LM) that operates over several streams of compressed discrete music representati…
Hybrid Transformers for Music Source Separation
Simon Rouard, Francisco Massa, Alexandre Défossez
A natural question arising in Music Source Separation (MSS) is whether long range contextual information is useful, or whether local acoustic features are sufficient. In other fiel…
Audio Language Modeling using Perceptually-Guided Discrete Representations
Felix Kreuk, Yaniv Taigman, Adam Polyak +4
In this work, we study the task of Audio Language Modeling, in which we aim at learning probabilistic models for audio that can be used for generation and completion. We use a stat…
High Fidelity Neural Audio Compression
Alexandre Défossez, Jade Copet, Gabriel Synnaeve +1
We introduce a state-of-the-art real-time, high-fidelity, audio codec leveraging neural networks. It consists in a streaming encoder-decoder architecture with quantized latent spac…
AudioGen: Textually Guided Audio Generation
Felix Kreuk, Gabriel Synnaeve, Adam Polyak +6
We tackle the problem of generating audio samples conditioned on descriptive text captions. In this work, we propose AaudioGen, an auto-regressive generative model that generates a…
Decoding speech perception from non-invasive brain recordings
Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin +2
Decoding speech from brain activity is a long-awaited goal in both healthcare and neuroscience. Invasive devices have recently led to major milestones in that regard: deep learning…
Hybrid Spectrogram and Waveform Source Separation
Alexandre Défossez
Source separation models either work on the spectrogram or waveform domain. In this work, we show how to perform end-to-end hybrid source separation, letting the model decide which…