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Crisis Connect: Sos Emergency Using Advanced-Deep Learning Speech Recognition Based on Vosk Engine
¹ Assistant professor, Department of Information Technology, Matrusri Engineering College, Hyderabad, Telangana, India. ² ³ ⁴ UG scholar, Department of Computer Engineering, Matrusri Engineering College, Hyderabad, Telangana, India.
Published Online: January-April 2026
Pages: 289-292
In a personal emergency, the transition from safety to crisis is instantaneous, often triggering a "motor-function freeze" that renders manual SOS triggers useless. This vulnerability is worsened by the "connectivity gap"—the failure of cloud-reliant apps in tunnels, basements, and dead-zones. This paper introduces Crisis Connect, a decentralized, network-agnostic framework that moves speech recognition to the device edge using the Vosk engine. By supporting English, Hindi, and Telugu without requiring data packets, and utilizing a Multi-Stage Vocal Verification Algorithm (MVVA) to filter environmental noise, the system ensures near-zero latency. Crisis Connect elevates the smartphone to an autonomous guardian, proving that the most reliable technology is the one that stays functional even when the world goes offline.
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