Implementation and Applications of WakeWords Integrated with Speaker Recognition: A Case Study

Alexandre Costa Ferro Filho, Elisa Ayumi Masasi de Oliveira, Iago Alves Brito, Pedro Martins Bittencourt
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Abstract

This paper explores the application of artificial intelligence techniques in audio and voice processing, focusing on the integration of wake words and speaker recognition for secure access in embedded systems. With the growing prevalence of voice-activated devices such as Amazon Alexa, ensuring secure and user-specific interactions has become paramount. Our study aims to enhance the security framework of these systems by leveraging wake words for initial activation and speaker recognition to validate user permissions. By incorporating these AI-driven methodologies, we propose a robust solution that restricts system usage to authorized individuals, thereby mitigating unauthorized access risks. This research delves into the algorithms and technologies underpinning wake word detection and speaker recognition, evaluates their effectiveness in real-world applications, and discusses the potential for their implementation in various embedded systems, emphasizing security and user convenience. The findings underscore the feasibility and advantages of employing these AI techniques to create secure, user-friendly voice-activated systems.
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WakeWords 与说话人识别整合的实施与应用:案例研究
本文探讨了人工智能技术在音频和语音处理中的应用,重点是在嵌入式系统中整合唤醒词和扬声器识别以实现安全访问。随着亚马逊 Alexa 等声控设备的日益普及,确保安全和针对特定用户的交互变得至关重要。我们的研究旨在利用唤醒词进行初始激活和扬声器识别来验证用户权限,从而增强这些系统的安全框架。通过结合这些人工智能驱动的方法,我们提出了一种稳健的解决方案,该方案可将系统的使用权限制在经授权的个人身上,从而降低未经授权访问的风险。本研究深入探讨了唤醒词检测和说话人识别的算法和技术,评估了它们在实际应用中的有效性,并讨论了它们在各种嵌入式系统中的应用潜力,同时强调了安全性和用户便利性。研究结果强调了采用这些人工智能技术创建安全、用户友好的声控系统的可行性和优势。
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