4 citations · 10 across the 12 of their papers we have counts for
9 papers · 1 filter
Few-Shot Keyword Spotting from Mixed Speech
Junming Yuan, Ying Shi, LanTian Li +2
Few-shot keyword spotting (KWS) aims to detect unknown keywords with limited training samples. A commonly used approach is the pre-training and fine-tuning framework. While effecti…
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…
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…
An Investigation of Distribution Alignment in Multi-Genre Speaker Recognition
Zhenyu Zhou, Junhui Chen, Namin Wang +2
Multi-genre speaker recognition is becoming increasingly popular due to its ability to better represent the complexities of real-world applications. However, a major challenge is t…
Multi-Domain Adaptation by Self-Supervised Learning for Speaker Verification
Wan Lin, Lantian Li, Dong Wang
In real-world applications, speaker recognition models often face various domain-mismatch challenges, leading to a significant drop in performance. Although numerous domain adaptat…