- Co-founder and Chief Science Officer, Gradium1
- Co-founder; leads research projects (listed as Head of Research on the team page), Kyutai12
Alexandre Défossez is a co-founder and the Chief Science Officer of Gradium, which builds voice AI models, and a co-founder of Kyutai, an open-science AI lab where Défossez continues to lead research projects; Kyutai's team page lists Défossez as Head of Research. Before Kyutai, Défossez spent three years as a research scientist at FAIR at Meta, leading the music generation work behind MusicGen and co-leading development of the AudioCraft framework. Défossez is first author of the EnCodec neural audio codec paper and of the Moshi speech-text foundation model paper; the Moshi repository releases its code under MIT and Apache licenses and its model weights under CC-BY 4.0.12345678
At a glance
- Current roles
- Co-founder and Chief Science Officer +1 more
- Work listed
- 2
- Sources cited
- 9
- Profile reviewed
Career
Alexandre Défossez was a CIFRE PhD student at FAIR and the Sierra team at INRIA, supervised by Léon Bottou and Nicolas Usunier of FAIR and Francis Bach of INRIA. Défossez then spent three years as a research scientist at FAIR, leading the music generation effort that produced MusicGen and co-leading development of the AudioCraft framework.1
Défossez co-founded Kyutai, an AI lab focused on open-source and open-science work, where Défossez continues to lead research projects, and is listed on Kyutai's team page as Head of Research. Défossez's homepage now also presents Défossez as a co-founder and Chief Science Officer of Gradium, a company that builds voice AI models.12
Research
Défossez's research covers generative music and speech models suited to low-latency interactive use across several modalities, as well as reinforcement learning for such models. Earlier work includes the Demucs music source separation models, real-time speech enhancement in the waveform domain, and theoretical papers on stochastic optimization, including a convergence proof for Adam and Adagrad.1
Défossez is first author of the EnCodec neural audio compression paper (2022) and last author of the MusicGen paper on simple and controllable music generation (2023), both from Meta AI. At Kyutai, Défossez is first author of the 2024 Moshi paper, a speech-text foundation model for real-time, full-duplex spoken dialogue, and has co-authored follow-up work on simultaneous speech-to-speech translation and on retrieval for full-duplex speech models.345961
Open-source work
Défossez's homepage lists the open-source software Défossez has worked on, including Moshi and its Mimi streaming audio codec, AudioCraft, EnCodec, Demucs, the Denoiser real-time speech enhancement tool, the Julius signal-processing library for PyTorch, and MuScriptor for multi-instrument music transcription. The AudioCraft repository releases its code under the MIT license, and the Moshi repository releases code under MIT and Apache licenses with model weights under CC-BY 4.0.187
Work and contributions
AudioCraft (EnCodec and MusicGen) Open-source code
Co-led development of the AudioCraft framework, per Défossez's homepage. Défossez is first author of the EnCodec paper (2022) and a core-team author of the MusicGen paper (2023); the AudioCraft repository releases its code under the MIT license and its model weights under CC-BY-NC 4.0.13598
Moshi Open weights
First author of the Moshi paper (2024), a speech-text foundation model for real-time dialogue. The Moshi repository provides the code under MIT and Apache licenses and states that the model weights are released under CC-BY 4.0.67
Timeline
- Published a paper with Francis Bach on constant step size least-mean-square at AISTATS 2015.1
- Presented SING, a symbol-to-instrument neural generator, at NeurIPS (then NIPS) 2018.1
- Posted the Demucs preprints on separating music sources in the waveform domain.1
- Published real-time speech enhancement in the waveform domain at Interspeech 2020.1
- Posted the EnCodec paper, "High Fidelity Neural Audio Compression," as first author.3
- Posted the MusicGen paper, "Simple and Controllable Music Generation," later presented at NeurIPS 2023.51
- Posted the Moshi paper on a speech-text foundation model for real-time dialogue as first author.6
- Co-authored MoshiRAG and a paper on simultaneous speech-to-speech translation without aligned data at ICML 2026.1
Other documented roles
Roles the sources document that are not confirmed as current.
- Research scientist at FAIR for three years, leading the music generation effort (MusicGen), Meta (FAIR)14
Where they work
Related people
- Xu TanSpeech and audio · Image, video, and 3D generation
- Wei-Ning HsuSpeech and audio · Multimodal models
- Jade CopetImage, video, and 3D generation · Speech and audio
- David HarwathSpeech and audio · Multimodal models
- RJ Skerry-RyanSpeech and audio · Image, video, and 3D generation
- Saining XieImage, video, and 3D generation · Multimodal models
- Heiga ZenSpeech and audio · Image, video, and 3D generation
- Sanyuan ChenSpeech and audio · Image, video, and 3D generation
- Jiaming SongImage, video, and 3D generation · Multimodal models
- Alexei BaevskiSpeech and audio · Multimodal models
Suggest a correction or removal
Profiles cover public professional work only, and each statement cites a source. If something is out of date, missing or wrong, tell us and link a source. People can also ask for their profile to be corrected or removed.
References
9 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026
- Alexandre Défossez — AI homepage
- Kyutai — Team
- High Fidelity Neural Audio Compression (arXiv 2210.13438)
- High Fidelity Neural Audio Compression — paper PDF (author affiliations: Meta AI, FAIR Team)
- Simple and Controllable Music Generation (arXiv 2306.05284)
- Moshi: a speech-text foundation model for real-time dialogue (arXiv 2410.00037)
- kyutai-labs/moshi README and license section
- facebookresearch/audiocraft README and license section
- Simple and Controllable Music Generation — paper PDF (core-team markers; author affiliation: Meta AI)