Kavli Affiliate: Zhuo Li
| First 5 Authors: Yuxiang Zhang, Zhuo Li, Wenchao Wang, Pengyuan Zhang,
| Summary:
Based on the assumption that there is a correlation between anti-spoofing and
speaker verification, a Total-Divide-Total integrated Spoofing-Aware Speaker
Verification (SASV) system based on pre-trained automatic speaker verification
(ASV) system and integrated scoring module is proposed and submitted to the
SASV 2022 Challenge. The training and scoring of ASV and anti-spoofing
countermeasure (CM) in current SASV systems are relatively independent,
ignoring the correlation. In this paper, by leveraging the correlation between
the two tasks, an integrated SASV system can be obtained by simply training a
few more layers on the basis of the baseline pre-trained ASV subsystem. The
features in pre-trained ASV system are utilized for logical access spoofing
speech detection. Further, speaker embeddings extracted by the pre-trained ASV
system are used to improve the performance of the CM. The integrated scoring
module takes the embeddings of the ASV and anti-spoofing branches as input and
preserves the correlation between the two tasks through matrix operations to
produce integrated SASV scores. Submitted primary system achieved equal error
rate (EER) of 3.07% on the development dataset of the SASV 2022 Challenge and
4.30% on the evaluation part, which is a 25% improvement over the baseline
systems.
| Search Query: ArXiv Query: search_query=au:”Zhuo Li”&id_list=&start=0&max_results=10