.png){kind=icon}
返回
Deep correlation network for synthetic speech detection
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2024.111413.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Synthetic speech is becoming increasingly rampant, and automatic speaker verification (ASV) systems are vulnerable to its attacks. However, most current synthetic speech detection methods focus on the influence of a single feature in the detection. Since different features can represent the difference between real speech and synthetic speech to a certain extent, there must be common information between different types of features. Effectively finding and fully utilizing this information will facilitate the extraction of better discriminative features and achieve improved performance. Based on the above analysis, we propose a deep correlation network (DCN) to learn the latent common information between different embeddings. It consists of two parts, the bi-parallel network and the correlation learning network. Bi-parallel networks consist of different neural models to learn the middle-level representations from front-end acoustical features. The correlation learning network is the core part of the DCN and is proposed to explore the common information between the above middle-level features. The common information obtained after DCN processing have better discriminative ability for synthetic speech detection. Experimental results show that the proposed DCN can significantly improve the performance of synthetic speech detection system on ASVspoof 2019 and ASVspoof 2021 logical access sub -challenge.
Keyword:
Synthetic speech detection
Deep correlation network
Correlation learning network
Common embedding
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
暂无机构信息
引用论文
Investigation of Linear and Nonlinear Properties of a Heartbeat Time Series Using Multiscale Rényi Entropy.png)
Entropy
OAAI
EntropyIF0
OAAI分享收藏分享收藏AVFakeNet: A unified end-to-end Dense Swin Transformer deep learning model for audio-visual deepfakes detectionAVFakeNet: 用于视听deepfakes检测的统一端到端密集Swin Transformer深度学习模型
PREAI
分享收藏
查看更多内容