Speaker individuality information is among the most critical elements within speech signals.
By thoroughly and accurately modeling this information, it can be utilized in various …

ASVspoof 5 is the fifth edition in a series of challenges that promote the study of speech
spoofing and deepfake attacks, and the design of detection solutions. Compared to previous …

Effective fusion of multi-scale features is crucial for improving speaker verification
performance. While most existing methods aggregate multi-scale features in a layer-wise …

This paper introduces ESPnet-SPK, a toolkit designed with several objectives for training
speaker embedding extractors. First, we provide an open-source platform for researchers in …

Trained on 680,000 h of massive speech data, Whisper is a multitasking, multilingual
speech foundation model demonstrating superior performance in automatic speech …

The residual neural networks (ResNet) demonstrate the impressive performance in
automatic speaker verification (ASV). They treat the time and frequency dimensions equally …

This paper focuses on the application of Conformers in speaker verification. Conformers,
initially designed for Automatic Speech Recognition (ASR), excel at modeling both local and …

Spoofing detection is today a mainstream research topic. Standard metrics can be applied to
evaluate the performance of isolated spoofing detection solutions and others have been …

Currently, ECAPA-TDNN is one of the state-of-the-art deep models for automatic speaker
verification (ASV). However, it focuses too much on local feature extraction with fixed local …

In this paper, we introduce a large-scale and high-quality audiovisual speaker verification
dataset, named VoxBlink. We propose an innovative and robust automatic audio-visual data …