This paper introduces RawBoost, a data boosting and augmentation method for the design
of more reliable spoofing detection solutions which operate directly upon raw waveform …

This paper describes the system of USTC-NERCSLIP submitted to the track 1.2 of the
second Audio Deepfake Detection Challenge (ADD 2023). Our system consists of a …

We propose an approach to extract speaker embeddings that are robust to speaking style
variations in text-independent speaker verification. Typically, speaker embedding extraction …

The effects of speaking-style variability on automatic speaker verification were investigated
using the UCLA Speaker Variability database which comprises multiple speaking styles per …

Despite the great success of speaker recognition models based on deep neural networks,
deploying a pre-trained model in real-world scenarios often leads to significant performance …

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 …

Mismatch between enrollment and test conditions causes serious performance degradation
on speaker recognition systems. This paper presents a statistics decomposition (SD) …

Voice biometric systems are being used in various applications for secure user
authentication using automatic speaker verification technology. However, these systems are …

Domain mismatch often occurs in real applications and causes serious performance
reduction on speaker verification systems. The common wisdom is to collect cross-domain …

Domain adaptation is often hampered by exceedingly small target datasets and inaccessible
source data. These conditions are prevalent in speech verification, where privacy policies …