22 citations · 42 across the 34 of their papers we have counts for
6 papers · 1 filter
State-of-the-art Embeddings with Video-free Segmentation of the Source VoxCeleb Data
Sara Barahona, Ladislav Mošner, Themos Stafylakis +4
In this paper, we refine and validate our method for training speaker embedding extractors using weak annotations. More specifically, we use only the audio stream of the source Vox…
CA-MHFA: A Context-Aware Multi-Head Factorized Attentive Pooling for SSL-Based Speaker Verification
Junyi Peng, Ladislav Mošner, Lin Zhang +4
Self-supervised learning (SSL) models for speaker verification (SV) have gained significant attention in recent years. However, existing SSL-based SV systems often struggle to capt…
BUT Systems and Analyses for the ASVspoof 5 Challenge
Johan Rohdin, Lin Zhang, Oldřich Plchot +8
This paper describes the BUT submitted systems for the ASVspoof 5 challenge, along with analyses. For the conventional deepfake detection task, we use ResNet18 and self-supervised…
Challenging margin-based speaker embedding extractors by using the variational information bottleneck
Themos Stafylakis, Anna Silnova, Johan Rohdin +2
Speaker embedding extractors are typically trained using a classification loss over the training speakers. During the last few years, the standard softmax/cross-entropy loss has be…
Comparing Data Augmentation Methods for End-to-End Task-Oriented Dialog Systems
Christos Vlachos, Themos Stafylakis, Ion Androutsopoulos
Creating effective and reliable task-oriented dialog systems (ToDSs) is challenging, not only because of the complex structure of these systems, but also due to the scarcity of tra…
Do End-to-End Neural Diarization Attractors Need to Encode Speaker Characteristic Information?
Lin Zhang, Themos Stafylakis, Federico Landini +3
In this paper, we apply the variational information bottleneck approach to end-to-end neural diarization with encoder-decoder attractors (EEND-EDA). This allows us to investigate w…