4 accepted papers
The wav2vec 2.0 and integrated spectro-temporal graph attention network (AASIST) based countermeasure achieves great performance in speech anti-spoofing. However, current spoof speech detection systems have fixed training and evaluation durations, while the performance degrades significantly during…
The detection of spoofing speech generated by unseen algorithms remains an unresolved challenge. One reason for the lack of generalization ability is that traditional detecting systems follow the binary classification paradigm, which inherently assumes the possession of prior knowledge of spoofing s…
ECAPA-TDNN is currently the most popular TDNN-series model for speaker verification, which refreshed the state-of-the-art (SOTA) performance of TDNN models. However, one-dimensional convolution has a global receptive field over the feature channel. It destroys the time-frequency relevance of the spe…
To extract high speaker-sensitive embeddings from deep neural networks is still a challenge in the field of speaker recognition. This paper proposes a novel network that learns speaker embeddings from multiple temporal scales. This idea comes from the recent biological research that the human audito…