4 papers
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…
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…
LongTail-Swap: benchmarking language models' abilities on rare words
Robin Algayres, Charles-Ãric Saint-James, Mahi Luthra +6
Children learn to speak with a low amount of data and can be taught new words on a few-shot basis, making them particularly data-efficient learners. The BabyLM challenge aims at ex…
Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Dataset
Vasu Agrawal, Akinniyi Akinyemi, Kathryn Alvero +81
Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals. To develop socially intelligent…