Intelligent Access Control System Based on Voiceprint and Voice Technology

Peng Wang, Juanjuan Li, Hao Wang, Huaizhen Chen, Junjie Cao, Yi Xu, Junyue He
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Abstract

This system used STM32H750XBH6 as the main control, and ART -Pi multimedia expansion board equipped with ILI9488 capacitive touch screen, WM8988 audio chip and GC0328C camera. It realizes recording, recognition, display, imposter capture and telescopic rod connection for door lock control. Based on convolutional neural network (CNN) and STM32 Cube. AI toolkit, voiceprint model was built and deployed to STM32H750XBH6. Combining Mel-Frequency Cepstral Coefficients (MFCC) and DTW algorithm, voice recognition function was realized. Through dual authentication of voiceprint verification and voice recognition, the system guaranteed high security. What is more, the system was equipped with a WIFI module, and the administrator can log in to the Onenet website to view the access control information. If there are three consecutive recognition errors, the system automatically capture the person and save the fake authentication certificate. After several improvements, the system can operate normally. The accuracy rate of voiceprint recognition and voice recognition were 97.83% and 96.00% respectively and the overall accuracy rate was 93.50%. Compared with traditional password access and card access, the system did not have problems of leak and lose. It provided users with high-security, true-intention, low-cost, and weak-privacy authentication services.
基于声纹和语音技术的智能门禁系统
本系统采用STM32H750XBH6作为主控器件,采用ART -Pi多媒体扩展板,配以ILI9488电容触摸屏、WM8988音频芯片和GC0328C摄像头。实现了门锁控制的记录、识别、显示、抓伪、伸缩杆连接等功能。基于卷积神经网络(CNN)和STM32 Cube。构建AI工具箱,声纹模型并部署到STM32H750XBH6上。结合Mel-Frequency倒谱系数(MFCC)和DTW算法,实现了语音识别功能。通过声纹验证和语音识别双重认证,保证了系统的高安全性。此外,系统还配备了WIFI模块,管理员可以登录Onenet网站查看门禁信息。如果连续三次识别错误,系统会自动抓人并保存假认证证书。经过多次改进,系统可以正常运行。声纹识别和语音识别准确率分别为97.83%和96.00%,总体准确率为93.50%。与传统的密码访问和卡访问相比,该系统不存在泄露和丢失的问题。为用户提供高安全性、真实意图、低成本、弱私密性的认证服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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