Maureen de Seyssel

🎉 Super happy to announce that a significant part of @LavechinMarvin's and my PhD research on modelling early language acquisition has finally been published in Developmental Science! 📄 doi.org/10.1111/desc.1… (OS version : onlinelibrary.wiley.com/share/author/9…) 🧵1/7

New preprint! In this work led by @MariaAndreaCruz during her internship at Apple, and with the help of Jie Chi and Zakaria Aldeneh, we show that visual grounding helps reduce the multilingual gap present in self-supervised speech models. arxiv.org/abs/2509.17523

Mar\'ia Andrea Cruz Bland\'on, Zakaria Aldeneh, Jie Chi, Maureen de Seyssel, "Leveraging Audio-Visual Data to Reduce the Multilingual Gap in Self-Supervised Speech Models," arxiv.org/abs/2509.17523

🎙️Slides from our @ISCAInterspeech tutorial “Speech Technology Meets Early Language Acquisition” (with Emmanuel Dupoux & Okko Räsänen) are online: zenodo.org/records/170182… 
 We hope they’re useful for anyone interested in connecting speech tech and early language learning!

In Vienna for ACL 2025! 🇦🇹 Come chat about speech, multilinguality, and cognitive modelling : I’ll be at the Apple booth Tuesday 1:30–3:30. #ACL2025NLP

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⚠️ Correction: The tutorial is on August 17th (not September 21)

We’ll show how bridging speech processing and psycholinguistics benefits both fields, and why speech researchers (you!) should care. Collab. between ENS/Meta (Emmanuel Dupoux), Tampere University (Okko Räsänen) and Apple (me). Hope to see many of you on September 21! (2/2)

Now that @ISCAInterspeech registration is open, time for some shameless promo! Sign-up and join our Interspeech tutorial: Speech Technology Meets Early Language Acquisition: How Interdisciplinary Efforts Benefit Both Fields. 🗣️👶 interspeech2025.org/tutorials ⬇️ (1/2)

New preprint out! 👇 We adapt the ABX task, commonly used in speech models, to investigate how multilingual text models represent form (language) vs content (meaning). 📄 arxiv.org/pdf/2505.17747 🙌 With Jie Chi, Skyler Seto, @maartjeterhoeve, Masha Fedzechkina & @natschluter

Equally looking forward to talking about formal languages for LLM pretraining and evaluation at Apple ML Research in Copenhagen next week:

@ansgarendress In this work, we investigate whether learning statistical regularities in speech supports word learning, and find that while people can detect these regularities, they rarely remember the words; suggesting a dissociation between pattern learning and memory. Check it out!

This work was primarily carried out by @ansgarendress, who also gave me my first taste of research, of cognition, and even introduced me to programming. Couldn't have asked for a better introduction!

New paper out in Cognition! 🎉 This one actually includes some of my (very) early work: my first-ever research project as an undergrad psychology student, now a decade ago. Nice to see it finally in print! 👉 authors.elsevier.com/sd/article/S00…

@LavechinMarvin 🤩

Glad to share this new study comparing the performance and biases of the LENA and ACLEW algorithms in analyzing language environments in Down, Fragile X, Angelman syndromes, and populations at elevated likelihood for autism 👶📄 osf.io/preprints/psya… 🧵1/12

🚀 We're hiring an ML Researcher! 🚀 If you're an expert in LLM alignment & personalization and want to work on a world-class research team, apply here 👉 lnkd.in/gU9yeivi Know someone who’d be a great fit? Tag them! #MachineLearning #AI #Apple

🥳 A huge thank you to all of our co-authors @hadwarez, @CristiaAlex, @hbredin, Guillaume Wisnewski & Emmanuel Dupoux, and of course to a larger extent to everyone in the @CoML_ENS team! 🧵7/7

💡Finally, we aim to illustrate with this research how advanced computational models can simulate broad and realistic language learning, and as such help advance psycholinguistic research. For a theoretical take, check our other paper ⬇ 📄cambridge.org/core/journals/… 🧵6/7

🎉 Super happy to announce that a significant part of @LavechinMarvin's and my PhD research on modelling early language acquisition has finally been published in Developmental Science! 📄 doi.org/10.1111/desc.1… (OS version : onlinelibrary.wiley.com/share/author/9…) 🧵1/7