most citedInvestigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification

12 citations · 25 across the 8 of their papers we have counts for

collaborators

10 papers

eess.AS20201 cited

Distortionless Multi-Channel Target Speech Enhancement for Overlapped Speech Recognition

Bo Wu, Meng Yu, Lianwu Chen +4

Speech enhancement techniques based on deep learning have brought significant improvement on speech quality and intelligibility. Nevertheless, a large gain in speech quality measur…

eess.AS20203 cited

Speaker Independent and Multilingual/Mixlingual Speech-Driven Talking Head Generation Using Phonetic Posteriorgrams

Huirong Huang, Zhiyong Wu, Shiyin Kang +9

Generating 3D speech-driven talking head has received more and more attention in recent years. Recent approaches mainly have following limitations: 1) most speaker-independent meth…

eess.AS202012 cited

Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification

Xu Li, Na Li, Jinghua Zhong +5

Recently adversarial attacks on automatic speaker verification (ASV) systems attracted widespread attention as they pose severe threats to ASV systems. However, methods to defend a…

eess.AS2020

End-to-End Multi-Look Keyword Spotting

Meng Yu, Xuan Ji, Bo Wu +2

The performance of keyword spotting (KWS), measured in false alarms and false rejects, degrades significantly under the far field and noisy conditions. In this paper, we propose a…

eess.AS20202 cited

Transferring Source Style in Non-Parallel Voice Conversion

Songxiang Liu, Yuewen Cao, Shiyin Kang +5

Voice conversion (VC) techniques aim to modify speaker identity of an utterance while preserving the underlying linguistic information. Most VC approaches ignore modeling of the sp…

eess.AS2020

Enhancing End-to-End Multi-channel Speech Separation via Spatial Feature Learning

Rongzhi Gu, Shi-Xiong Zhang, Lianwu Chen +5

Hand-crafted spatial features (e.g., inter-channel phase difference, IPD) play a fundamental role in recent deep learning based multi-channel speech separation (MCSS) methods. Howe…