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

TL;DR

This paper investigates integrating wake words with speaker recognition to improve security and user authentication in voice-activated embedded systems, demonstrating practical effectiveness and implementation strategies.

Contribution

It introduces a combined approach of wake word detection and speaker recognition for enhanced security in embedded voice systems, with real-world evaluation.

Findings

Effective wake word and speaker recognition algorithms demonstrated

Enhanced security by restricting access to authorized users

Feasibility of implementation in embedded systems confirmed

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.