100 citations · 127 across the 7 of their papers we have counts for
9 papers
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…
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…
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.…
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…
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…
The "Sprekend Nederland" project and its application to accent location
David A. van Leeuwen, Rosemary Orr
This paper describes the data collection effort that is part of the project Sprekend Nederland (The Netherlands Talking), and discusses its potential use in Automatic Accent Locati…
Constrained speaker linking
David A. van Leeuwen, Niko Brümmer
In this paper we study speaker linking (a.k.a.\ partitioning) given constraints of the distribution of speaker identities over speech recordings. Specifically, we show that the int…
A comparison of linear and non-linear calibrations for speaker recognition
Niko Brümmer, Albert Swart, David van Leeuwen
In recent work on both generative and discriminative score to log-likelihood-ratio calibration, it was shown that linear transforms give good accuracy only for a limited range of o…
The distribution of calibrated likelihood-ratios in speaker recognition
David A. van Leeuwen, Niko Brümmer
This paper studies properties of the score distributions of calibrated log-likelihood-ratios that are used in automatic speaker recognition. We derive the essential condition for c…