This paper presents a lightweight, cascaded GMM-DTW dual-factor voice lock system for resource-constrained edge environments. By utilizing a shared MFCC feature space, the framework implements a sequential defense mechanism combining GMM speaker screening and DTW passphrase verification. To counter presentation threats without extra hardware, a dynamic joint absolute-relative margin constraint is integrated into the GMM classification space, limiting the physical imposter and high-fidelity replay attack False Acceptance Rates (FAR) to 2.73% and 6.67%, respectively, with a legitimate False Rejection Rate (FRR) of 16.67%. Due to Sakoe-Chiba window optimization, the global end-to-end processing latency under temporal stress is rigidly bounded at 9.82ms on a single-core CPU, comprising 1.51ms for feature extraction, 0.54ms for GMM scoring, and 7.77ms for worst-case DTW matching. These empirical benchmarks demonstrate the viability of white-box acoustic cascades for secure, deterministic real-time deployment on low-power edge nodes.

翻译：本文针对资源受限的边缘环境，提出一种轻量化的级联GMM-DTW双因子语音锁系统。通过共享MFCC特征空间，该框架实现了结合GMM说话人筛选与DTW口令验证的序贯防御机制。为在不增加额外硬件条件下抵御演示攻击，我们在GMM分类空间中引入动态联合绝对-相对间隔约束，将物理模拟攻击与高保真重放攻击的误接受率分别限制在2.73%和6.67%，同时合法用户的误拒绝率为16.67%。得益于Sakoe-Chiba窗口优化，在时间压力下全局端到端处理延迟被严格限制在9.82ms（单核CPU），其中特征提取耗时1.51ms、GMM评分耗时0.54ms、最坏情况DTW匹配耗时7.77ms。这些实证基准证明了白盒声学级联方法在低功耗边缘节点上实现安全、确定性实时部署的可行性。