Data on Machine Learning Discussed by Researchers at University of Salerno (Acou stic Features Analysis for Explainable Machine Learning-based Audio Spoofing Det ection)
Data on Machine Learning Discussed by Researchers at University of Salerno (Acou stic Features Analysis for Explainable Machine Learning-based Audio Spoofing Det ection)
萨勒诺大学研究人员讨论的机器学习数据（可解释机器学习音频欺骗检测的acoustic特征分析）
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摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布马学习的新报告。根据新闻报道NewsRx Ed Itors在意大利菲西亚诺发表的一篇文章中指出，“合成语音生成的快速发展”而且，音频处理技术带来了重大挑战，引起了社会和安全方面的关注由于假冒的风险和udio深度假货的扩散。本研究介绍了基于轻量级机器学习(ml)的框架，旨在有效区分真正和伪造的录音。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reporting outof Fisciano, Italy, by NewsRx ed itors, research stated, “The rapid evolution of synthetic voice generationand a udio manipulation technologies poses significant challenges, raising societal an d security concernsdue to the risks of impersonation and the proliferation of a udio deepfakes. This study introduces alightweight machine learning (ML)-based framework designed to effectively distinguish between genuineand spoofed audio recordings.”
Key words
Fisciano/Italy/Europe/Cybersecurity/Cyborgs/Emerging Technologies/Machine Learning/University of Salerno
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