AI RESEARCH
SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation
arXiv CS.CL
•
ArXi:2512.21204v2 Announce Type: replace 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-supervised speech models. To address this gap, this paper