Vox-1-H
Emerging5papers using it
2022first seen
The 'Vox1-H' dataset is a benchmark used to evaluate speaker verification performance, containing a set of test samples for assessing the effectiveness of models in distinguishing between different speakers.
Papers using Vox-1-H (5)
- An Attention-based Backend Allowing Efficient Fine-tuning Of Transformer Models For Speaker VerificationEnhancing 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-SpoofingAn 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 adapters