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20212025
most citedFine-tuning wav2vec2 for speaker recognition

100 citations · 114 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SD2025

Self-supervised learning of speech representations with Dutch archival data

Nik Vaessen, Roeland Ordelman, David A. van Leeuwen

This paper explores the use of Dutch archival television broadcast data for self-supervised learning of speech foundation models, specifically wav2vec 2.0. We first study data qual…

cs.SD2024

The Effect of Batch Size on Contrastive Self-Supervised Speech Representation Learning

Nik Vaessen, David A. van Leeuwen

Foundation models in speech are often trained using many GPUs, which implicitly leads to large effective batch sizes. In this paper we study the effect of batch size on pre-trainin…

eess.AS2023★ 2 cited

Beyond Neural-on-Neural Approaches to Speaker Gender Protection

Loes van Bemmel, Zhuoran Liu, Nik Vaessen +1

Recent research has proposed approaches that modify speech to defend against gender inference attacks. The goal of these protection algorithms is to control the availability of inf…

eess.AS2023★ 3 cited

Speaker and Language Change Detection using Wav2vec2 and Whisper

Tijn Berns, Nik Vaessen, David A. van Leeuwen

We investigate recent transformer networks pre-trained for automatic speech recognition for their ability to detect speaker and language changes in speech. We do this by simply add…

cs.SD2023

Towards multi-task learning of speech and speaker recognition

Nik Vaessen, David A. van Leeuwen

We study multi-task learning for two orthogonal speech technology tasks: speech and speaker recognition. We use wav2vec2 as a base architecture with two task-specific output heads.…

cs.SD2022★ 9 cited

Training speaker recognition systems with limited data

Nik Vaessen, David A. van Leeuwen

This work considers training neural networks for speaker recognition with a much smaller dataset size compared to contemporary work. We artificially restrict the amount of data by…

cs.SD2021★ 100 cited

Fine-tuning wav2vec2 for speaker recognition

Nik Vaessen, David A. van Leeuwen

This paper explores applying the wav2vec2 framework to speaker recognition instead of speech recognition. We study the effectiveness of the pre-trained weights on the speaker recog…