most citedAn attention-based backend allowing efficient fine-tuning of transformer models for speaker verification

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing eess.ASShow all

2 papers · 1 filter

eess.AS2022

Parameter-efficient transfer learning of pre-trained Transformer models for speaker verification using adapters

Junyi Peng, Themos Stafylakis, Rongzhi Gu +4

Recently, the pre-trained Transformer models have received a rising interest in the field of speech processing thanks to their great success in various downstream tasks. However, m…

eess.AS2022★ 1 cited

An attention-based backend allowing efficient fine-tuning of transformer models for speaker verification

Junyi Peng, Oldrich Plchot, Themos Stafylakis +3

In recent years, self-supervised learning paradigm has received extensive attention due to its great success in various down-stream tasks. However, the fine-tuning strategies for a…