Web: http://arxiv.org/abs/2205.06182

May 13, 2022, 1:11 a.m. | Satwinder Singh, Ruili Wang, Feng Hou

cs.LG updates on arXiv.org arxiv.org

We propose a new meta learning based framework for low resource speech
recognition that improves the previous model agnostic meta learning (MAML)
approach. The MAML is a simple yet powerful meta learning approach. However,
the MAML presents some core deficiencies such as training instabilities and
slower convergence speed. To address these issues, we adopt multi-step loss
(MSL). The MSL aims to calculate losses at every step of the inner loop of MAML
and then combines them with a weighted importance …

arxiv learning meta speech speech recognition

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