2 citations · 3 across the 6 of their papers we have counts for
6 papers
Probing Self-supervised Learning Models with Target Speech Extraction
Junyi Peng, Marc Delcroix, Tsubasa Ochiai +4
Large-scale pre-trained self-supervised learning (SSL) models have shown remarkable advancements in speech-related tasks. However, the utilization of these models in complex multi-…
Target Speech Extraction with Pre-trained Self-supervised Learning Models
Junyi Peng, Marc Delcroix, Tsubasa Ochiai +3
Pre-trained self-supervised learning (SSL) models have achieved remarkable success in various speech tasks. However, their potential in target speech extraction (TSE) has not been…
Improving Speaker Verification with Self-Pretrained Transformer Models
Junyi Peng, Oldřich Plchot, Themos Stafylakis +3
Recently, fine-tuning large pre-trained Transformer models using downstream datasets has received a rising interest. Despite their success, it is still challenging to disentangle t…
Probing Deep Speaker Embeddings for Speaker-related Tasks
Zifeng Zhao, Ding Pan, Junyi Peng +1
Deep speaker embeddings have shown promising results in speaker recognition, as well as in other speaker-related tasks. However, some issues are still under explored, for instance,…
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…
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…