4 papers · 1 filter
An Investigation on Speaker Augmentation for End-to-End Speaker Extraction
Zhenghai You, Zhenyu Zhou, Lantian Li +1
Target confusion, defined as occasional switching to non-target speakers, poses a key challenge for end-to-end speaker extraction (E2E-SE) systems. We argue that this problem is la…
Neural Scoring: A Refreshed End-to-End Approach for Speaker Recognition in Complex Conditions
Wan Lin, Junhui Chen, Tianhao Wang +3
Modern speaker verification systems primarily rely on speaker embeddings, followed by verification based on cosine similarity between the embedding vectors of the enrollment and te…
A Comprehensive Investigation on Speaker Augmentation for Speaker Recognition
Zhenyu Zhou, Shibiao Xu, Shi Yin +2
Data augmentation (DA) has played a pivotal role in the success of deep speaker recognition. Current DA techniques primarily focus on speaker-preserving augmentation, which does no…
Adversarial Data Augmentation for Robust Speaker Verification
Zhenyu Zhou, Junhui Chen, Namin Wang +2
Data augmentation (DA) has gained widespread popularity in deep speaker models due to its ease of implementation and significant effectiveness. It enriches training data by simulat…