6 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
SpidR: Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision
Maxime Poli, Mahi Luthra, Youssef Benchekroun +8
The parallel advances in language modeling and speech representation learning have raised the prospect of learning language directly from speech without textual intermediates. This…
SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation
Mahi Luthra, Jiayi Shen, Maxime Poli +14
Human infants, with only a few hundred hours of speech exposure, acquire basic units of new languages, highlighting a striking efficiency gap compared to the data-hungry self-super…
BabyHuBERT: Multilingual Self-Supervised Learning for Segmenting Speakers in Child-Centered Long-Form Recordings
Théo Charlot, Tarek Kunze, Maxime Poli +3
Child-centered daylong recordings are essential for studying early language development, but existing speech models trained on clean adult data perform poorly due to acoustic and l…
fastabx: A library for efficient computation of ABX discriminability
Maxime Poli, Emmanuel Chemla, Emmanuel Dupoux
We introduce fastabx, a high-performance Python library for building ABX discrimination tasks. ABX is a measure of the separation between generic categories of interest. It has bee…