Contrastive Predictive Coding Based Feature for Automatic Speaker Verification
This is an incremental approach for speaker verification systems, potentially enhancing feature extraction in a domain-specific context.
The paper tackles the problem of improving automatic speaker verification by incorporating Contrastive Predictive Coding (CPC) features into standard systems, but no concrete results or numbers are provided as it describes ongoing work.
This thesis describes our ongoing work on Contrastive Predictive Coding (CPC) features for speaker verification. CPC is a recently proposed representation learning framework based on predictive coding and noise contrastive estimation. We focus on incorporating CPC features into the standard automatic speaker verification systems, and we present our methods, experiments, and analysis. This thesis also details necessary background knowledge in past and recent work on automatic speaker verification systems, conventional speech features, and the motivation and techniques behind CPC.