Papers by Youssef Benchekroun
SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation (2026.acl-long)
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Mahi Luthra, Jiayi Shen, Maxime Poli, Angelo Ortiz Tandazo, Yosuke Higuchi, Youssef Benchekroun, Martin Gleize, Charles-Éric Saint-James, Dongyan Lin, Phillip Rust, Angel Villar-Corrales, null Surya, Vanessa Stark, Rashel Moritz, Juan Pino, Yann LeCun, Emmanuel Dupoux
| Challenge: | Empirically, SpidR-Adapt achieves rapid gains in phonemic discriminability and downstream spoken language modeling scores . current self-supervised learning models require thousands of hours of training data to learn meaningful linguistic representations. |
| Approach: | They propose a bi-level optimization framework for rapid adaptation of speech units to new languages using minimal unlabeled data. |
| Outcome: | The proposed model achieves rapid gains in phonemic discriminability and spoken language modeling scores . it surpasses in-domain toplines after training on less than 1h of target-language audio . |
MauBERT: Universal Phonetic Inductive Biases for Few-Shot Acoustic Units Discovery (2026.acl-long)
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| Challenge: | MauBERT models learn from multilingual data to predict articulatory features or phones, resulting in language-independent phonetic representations. |
| Approach: | They introduce a multilingual extension of HuBERT that leverages articulatory features for robust cross-lingual phonetic representation learning. |
| Outcome: | The proposed model can predict phonetic features in 55 languages with minimal fine-tuning (10 hours of speech) it is more context-invariant than state-of-the-art models and adapts to unseen languages and casual speech with minimal self-supervised fine- tuning (10 hours) |
LongTail-Swap: benchmarking language models’ abilities on rare words (2025.findings-emnlp)
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Robin Algayres, Charles-Éric Saint-James, Mahi Luthra, Jiayi Shen, Youssef Benchekroun, Dongyan Lin, Rashel Moritz, Juan Pino, Emmanuel Dupoux
| Challenge: | LongTail-Swap is a benchmark that focuses on the tail of the word distribution, i.e., measures the ability of LMs to learn new words with very little exposure, like infants do. |
| Approach: | They introduce LongTail-Swap, a benchmark that measures the ability of language models to learn new words with very little exposure, like infants do. |
| Outcome: | The proposed benchmark measures the ability of language models to learn new words with very little exposure, like infants do. |