Vox-1-O
Emerging6papers using it
2022first seen
The 'Vox-1-O' dataset is a benchmark used to evaluate speaker verification performance, specifically measuring the effectiveness of models in distinguishing between different speakers.
Papers using Vox-1-O (6)
- Enhancing Speaker Verification with w2v-BERT 2.0 and Knowledge Distillation guided Structured PruningHybrid Pruning: In-Situ Compression of Self-Supervised Speech Models for Speaker Verification and Anti-SpoofingPCF: ECAPA-TDNN with Progressive Channel Fusion for Speaker VerificationAn attention-based backend allowing efficient fine-tuning of transformer
models for speaker verificationParameter-efficient transfer learning of pre-trained Transformer models
for speaker verification using adaptersESPnet-SPK: full pipeline speaker embedding toolkit with reproducible
recipes, self-supervised front-ends, and off-the-shelf models