1 citations · 3 across the 15 of their papers we have counts for
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An Investigation on Speaker Augmentation for End-to-End Speaker Extraction
Zhenghai You, Zhenyu Zhou, Lantian Li +1
Target confusion, defined as occasional switching to non-target speakers, poses a key challenge for end-to-end speaker extraction (E2E-SE) systems. We argue that this problem is la…
AlignVSR: Audio-Visual Cross-Modal Alignment for Visual Speech Recognition
Zehua Liu, Xiaolou Li, Chen Chen +3
Visual Speech Recognition (VSR) aims to recognize corresponding text by analyzing visual information from lip movements. Due to the high variability and weak information of lip mov…
Neural Scoring: A Refreshed End-to-End Approach for Speaker Recognition in Complex Conditions
Wan Lin, Junhui Chen, Tianhao Wang +3
Modern speaker verification systems primarily rely on speaker embeddings, followed by verification based on cosine similarity between the embedding vectors of the enrollment and te…
Quantitative Analysis of Audio-Visual Tasks: An Information-Theoretic Perspective
Chen Chen, Xiaolou Li, Zehua Liu +2
In the field of spoken language processing, audio-visual speech processing is receiving increasing research attention. Key components of this research include tasks such as lip rea…
Zero-Shot Fake Video Detection by Audio-Visual Consistency
Xiaolou Li, Zehua Liu, Chen Chen +3
Recent studies have advocated the detection of fake videos as a one-class detection task, predicated on the hypothesis that the consistency between audio and visual modalities of g…
SE/BN Adapter: Parametric Efficient Domain Adaptation for Speaker Recognition
Tianhao Wang, Lantian Li, Dong Wang
Deploying a well-optimized pre-trained speaker recognition model in a new domain often leads to a significant decline in performance. While fine-tuning is a commonly employed solut…
A Comprehensive Investigation on Speaker Augmentation for Speaker Recognition
Zhenyu Zhou, Shibiao Xu, Shi Yin +2
Data augmentation (DA) has played a pivotal role in the success of deep speaker recognition. Current DA techniques primarily focus on speaker-preserving augmentation, which does no…
How phonemes contribute to deep speaker models?
Pengqi Li, Tianhao Wang, Lantian Li +2
Which phonemes convey more speaker traits is a long-standing question, and various perception experiments were conducted with human subjects. For speaker recognition, studies were…
Adversarial Data Augmentation for Robust Speaker Verification
Zhenyu Zhou, Junhui Chen, Namin Wang +2
Data augmentation (DA) has gained widespread popularity in deep speaker models due to its ease of implementation and significant effectiveness. It enriches training data by simulat…
Pay Attention to Hard Trials
Lantian Li, Di Wang, Dong Wang
Performance of speaker recognition systems is evaluated on test trials. Although as crucial as rulers for tailors, trials have not been carefully treated so far, and most existing…
A Study on Decoupled Probabilistic Linear Discriminant Analysis
Di Wang, Lantian Li, Hongzhi Yu +1
Probabilistic linear discriminant analysis (PLDA) has broad application in open-set verification tasks, such as speaker verification. A key concern for PLDA is that the model is to…