Query-Efficient Adversarial Attack With Low Perturbation Against End-to-End Speech Recognition Systems-Reference-Cited by-同舟云学术

Query-Efficient Adversarial Attack With Low Perturbation Against End-to-End Speech Recognition Systems

Author:

Wang Shen¹^ORCID,Zhang Zhaoyang¹,Zhu Guopu¹^ORCID,Zhang Xinpeng²^ORCID,Zhou Yicong³^ORCID,Huang Jiwu⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

2. School of Computer Science, Fudan University, Shanghai, China

3. Department of Computer and Information Science, University of Macau, Taipa, Macau

4. Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China

Funder

National Defense Basic Scientific Research Program of China

National Natural Science Foundation of China

Science and Technology Development Fund, Macau SAR

University of Macau

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

Reference58 articles.

5. Deep speech: Scaling up end-to-end speech recognition;hannun;arXiv 1412 5567,2014

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