Assistant Professor at CentraleSupélec in Rennes, France. Signal processing and machine learning for audio.
Rennes, France
Joined September 2014
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Simon Leglaive retweeted
🎉 Our diffusion-model monograph 《The Principles of Diffusion Models》 now has an official website!
🔗 Link in thread
💡 Two highlights:
1️⃣ Blog Post: a big-picture walkthrough from diffusion models → fast generation & flow map models;
2️⃣ Teaching Guide: lightweight course prep notes for instructors using the book
Feel free to share + tag folks who may be interested.
If you’re considering using it for teaching, reach out please — happy to chat and help! 🚀
(w/ @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon)
Tired to go back to the original papers again and again? Our monograph: a systematic and fundamental recipe you can rely on!
📘 We’re excited to release 《The Principles of Diffusion Models》— with @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon.
It traces the core ideas that shaped diffusion modeling and explains how today’s models work, why they work, and where they’re heading.
🧵You’ll find the link and a few highlights in the thread.
We’d love to hear your thoughts and join some discussions!
⚡ Stay tuned for our markdown version, where you can drop your comments!
Simon Leglaive retweeted
What a speaker line up! Register (project.inria.fr/soraim/) if you want to hear these wonderful people.
Simon Leglaive retweeted
Sofiene Kammoun, Xavier Alameda-Pineda, Simon Leglaive, "Modeling strategies for speech enhancement in the latent space of a neural audio codec," arxiv.org/abs/2510.26299
Simon Leglaive retweeted
We are seeking reviewers for speech & language processing at ICASSP'26.
Please consider nominating yourself or a colleague, and help spread the word!
Reviewing is a great first step to contribute to the community :)
📢🌟🌟Call for ICASSP 2026 Speech and Language Processing Reviewer Nominations
Please submit new speech and language processing reviewer nominations for ICASSP 2026 using the form below.
docs.google.com/forms/d/1wty…
Simon Leglaive retweeted
🚨 Open PhD Position (fully funded) – Grenoble, France
Join us at @GipsaLab (@CNRS, @UGrenobleAlpes collab. @RobotLearnInria) to explore how Speech Language Models can learn like children: through physical and social interaction🧠🤖🎙️
Details 👉 tinyurl.com/bde988b3
Simon Leglaive retweeted
Enjoyed a great INTERSPEECH 2025 experience! (my first since 2019 at Austria😮💨) Kudos to the organizers!
Please find our tutorial slides here: voicemos-challenge-2023.gith…
Also if you work on MOS prediction make sure you check out SHEET! github.com/unilight/sheet
Simon Leglaive retweeted
New video on the details of diffusion models: youtu.be/iv-5mZ_9CPY
Produced by @welchlabs, this is the first in a small series of 3b1b this summer. I enjoyed providing editorial feedback throughout the last several months, and couldn't be happier with the result.
Simon Leglaive retweeted
@chimechallenge
⭐⭐ We are happy to announce the release of the tasks for the 9th CHiME Speech Separation and Recognition Challenge (CHiME-9).
⚡⚡ Please visit the CHiME Challenge website for details chimechallenge.org/ ⚡⚡
Simon Leglaive retweeted
PESTO 2.0 è rilasciato! 🥳🥳🥳
With Brazilian chef @torres_be_ (and others), we revisit this traditional italian sauce, invented in Milan at @ISMIRConf 2023 🇮🇹
And you can taste it in REAL-TIME at home (~5 ms latency) ⏱️
1/6
Simon Leglaive retweeted
``AnCoGen: Analysis, Control and Generation of Speech with a Masked Autoencoder,'' Samir Sadok, Simon Leglaive, Laurent Girin, Ga\"el Richard, Xavier Alameda-Pineda, ift.tt/eDFJaWg
Simon Leglaive retweeted
In my keynote at @ISMIRConf yesterday I played video messages from musicians asking the assembled AI researchers not to train on their music without their consent.
It’s testament to the respect the ISMIR community has for musicians that the reaction was overwhelmingly positive. Many in the AI music + MIR community reject unlicensed training, just like most musicians do.
Don’t think the debate is creators vs. the AI community. Many AI researchers feel very uncomfortable with the actions a handful of AI companies are taking.
Huge thanks to ISMIR for having me 🙏
Simon Leglaive retweeted
We are thrilled to announce the Interspeech 2025 URGENT Challenge, starting on 11/15!
Join us in building universal speech enhancement models to tackle in-the-wild speech data using large-scale, multilingual data. Details: urgent-challenge.github.io/u…
Simon Leglaive retweeted
During my postdoc at Cornell (2017–2020), i worked on machine listening of flight calls for bird migration monitoring as part of the NSF project BIRDVOX
This IEEE TASLP article concludes the project
hal.science/hal-04670882
Simon Leglaive retweeted
Great piece of work led by @FrancoisRozet in which we revisit the good old EM algorithm to learn diffusion models from corrupted data only. Bonus: This also includes a new posterior sampling scheme for diffusion models!
📢 Are you interested in diffusion models and inverse problems? Check out our new preprint "Learning Diffusion Priors from Observations by Expectation Maximization" with @g4ndry, François Lanusse and @glouppe! 🧵
arxiv.org/abs/2405.13712
Simon Leglaive retweeted
We're organizing a special issue at Computer Speech & Language about Multi-Speaker, Multi-Microphone, and Multi-Modal Distant Speech Recognition.
Deadline: December 2, 2024
sciencedirect.com/journal/co…
@chimechallenge
Simon Leglaive retweeted
Thrilled to have contributed to the evaluation of speech enhancement methods in the CHiME-7 UDASE task, now published in Computer Speech & Language. 📚🔊 #CHiMEChallenge
Read more: doi.org/10.1016/j.csl.2024.1…
Simon Leglaive retweeted
How can learned quantized representations help to address human mesh recovery?
In VQ-HPS, to be presented at #ECCV2024, we frame HMR as a classification task in a quantized latent space. (1/6)
Simon Leglaive retweeted
BUDDy: Single-Channel Blind Unsupervised Dereverberation with Diffusion Models
We present a fully unsupervised method for blind speech dereverberation using a diffusion prior and a parametric subband filter
Paper 📜 arxiv.org/abs/2405.04272
Audio/Code 🔊 uhh.de/sp-inf-buddy
Simon Leglaive retweeted
We’re happy to announce our recent JOSS paper! 🎉Soundata: Reproducible use of audio datasets
⚙️github.com/soundata/soundata
📄 joss.theoj.org/papers/10.211…
Simon Leglaive retweeted
"Model-based deep learning for music information research"
to appear in IEEE Signal Processing Magazine
with G. Richard, Y.-H. Yang, and M. Müller
I wrote about differentiable scattering transforms and perceptual–neural–physical sound matching (PNP)
hal.science/hal-04611461/
