3 papers
eess.AS2025
Bayesian Learning for Domain-Invariant Speaker Verification and Anti-Spoofing
Jin Li, Man-Wai Mak, Johan Rohdin +2
The performance of automatic speaker verification (ASV) and anti-spoofing drops seriously under real-world domain mismatch conditions. The relaxed instance frequency-wise normaliza…
eess.AS2024
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…
eess.AS2023
DiaCorrect: Error Correction Back-end For Speaker Diarization
Jiangyu Han, Federico Landini, Johan Rohdin +5
In this work, we propose an error correction framework, named DiaCorrect, to refine the output of a diarization system in a simple yet effective way. This method is inspired by err…