中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
  5. 模式分析与学习团队
SceneFake: An initial dataset and benchmarks for scene fake audio detection

文献类型：期刊论文

作者Yi, Jiangyan1; Wang, Chenglong1,2; Tao, Jianhua3,4; Zhang, Chu Yuan1; Fan, Cunhang5; Tian, Zhengkun1; Ma, Haoxin1; Fu, Ruibo1
刊名PATTERN RECOGNITION
出版日期2024-08-01
卷号152页码:12
关键词Scene manipulation Fake audio detection Speech enhancement SceneFake dateset
ISSN号0031-3203
DOI10.1016/j.patcog.2024.110468
通讯作者Yi, Jiangyan(jiangyan.yi@nlpr.ia.ac.cn)
英文摘要Many datasets have been designed to further the development of fake audio detection. However, fake utterances in previous datasets are mostly generated by altering timbre, prosody, linguistic content or channel noise of original audio. These datasets leave out a scenario, in which the acoustic scene of an original audio is manipulated with a forged one. It will pose a major threat to our society if some people misuse the manipulated audio with malicious purpose. Therefore, this motivates us to fill in the gap. This paper proposes such a dataset for scene fake audio detection named SceneFake, where a manipulated audio is generated by only tampering with the acoustic scene of an real utterance by using speech enhancement technologies. Some scene fake audio detection benchmark results on the SceneFake dataset are reported in this paper. In addition, an analysis of fake attacks with different speech enhancement technologies and signal-to-noise ratios are presented in this paper. The results indicate that scene fake utterances cannot be reliably detected by baseline models trained on the ASVspoof 2019 dataset. Although these models perform well on the SceneFake training set and seen testing set, their performance is poor on the unseen test set. The dataset2 and benchmark source codes3 are publicly available.
WOS关键词SPEAKER VERIFICATION ; SPEECH ENHANCEMENT ; IDENTIFICATION
资助项目National Natural Science Foundation China (NSFC)[62322120] ; National Natural Science Foundation China (NSFC)[62306316] ; National Natural Science Foundation China (NSFC)[U21B2010] ; National Natural Science Foundation China (NSFC)[62101553] ; National Natural Science Foundation China (NSFC)[62206278]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:001226983800001
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation China (NSFC)
源URL[http://ir.ia.ac.cn/handle/173211/58467]  
专题自动化研究所_模式识别国家重点实验室_模式分析与学习团队
通讯作者Yi, Jiangyan
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China
2.Univ Sci & Technol China, Hefei, Peoples R China
3.Tsinghua Univ, Dept Automat, Beijing, Peoples R China
4.Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol, Beijing, Peoples R China
5.Anhui Univ, Hefei, Peoples R China
推荐引用方式
GB/T 7714		 Yi, Jiangyan,Wang, Chenglong,Tao, Jianhua,et al. SceneFake: An initial dataset and benchmarks for scene fake audio detection[J]. PATTERN RECOGNITION,2024,152:12.
APA Yi, Jiangyan.,Wang, Chenglong.,Tao, Jianhua.,Zhang, Chu Yuan.,Fan, Cunhang.,...&Fu, Ruibo.(2024).SceneFake: An initial dataset and benchmarks for scene fake audio detection.PATTERN RECOGNITION,152,12.
MLA Yi, Jiangyan,et al."SceneFake: An initial dataset and benchmarks for scene fake audio detection".PATTERN RECOGNITION 152(2024):12.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。