most citedMulti-source Domain Adaptation for Text-independent Forensic Speaker Recognition

28 citations · 37 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD202228 cited

Multi-source Domain Adaptation for Text-independent Forensic Speaker Recognition

Zhenyu Wang, John H. L. Hansen

Adapting speaker recognition systems to new environments is a widely-used technique to improve a well-performing model learned from large-scale data towards a task-specific small-s…

cs.SD20229 cited

Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning

Zhenyu Wang, John H. L. Hansen

Automatic speaker verification systems are vulnerable to a variety of access threats, prompting research into the formulation of effective spoofing detection systems to act as a ga…

eess.AS2022

Impact of Naturalistic Field Acoustic Environments on Forensic Text-independent Speaker Verification System

Zhenyu Wang, John H. L. Hansen

Audio analysis for forensic speaker verification offers unique challenges in system performance due in part to data collected in naturalistic field acoustic environments where loca…

eess.AS2020

A multi-view approach for Mandarin non-native mispronunciation verification

Zhenyu Wang, John H. L. Hansen, Yanlu Xie

Traditionally, the performance of non-native mispronunciation verification systems relied on effective phone-level labelling of non-native corpora. In this study, a multi-view appr…

eess.AS2020

Cross-domain Adaptation with Discrepancy Minimization for Text-independent Forensic Speaker Verification

Zhenyu Wang, Wei Xia, John H. L. Hansen

Forensic audio analysis for speaker verification offers unique challenges due to location/scenario uncertainty and diversity mismatch between reference and naturalistic field recor…