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Crisis Connect: Sos Emergency Using Advanced-Deep Learning Speech Recognition Based on Vosk Engine
K. Mounika1
CH.P.Chaitanya2
P.Pranay Sai3
R.Lahithi4
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
Cite this article
No DOIReferences
1. Zhou, Y., et al. Beyond the Panic Button: Limitations of Manual UI in High-Stress Scenarios. Journal of Safety Research. 2019; 71: 121–129.
2. Koubaa, A., et al. A Service-Oriented Architecture for Critical IoT Applications. IEEE Access. 2018; 6: 1293–1305.
3. Debatin, N., et al. Evaluation of Offline Speech Recognition Engines for Embedded Systems. International Journal of Embedded Systems.
2021; 14(2): 110–118.
4. Chatterjee, S., & Misra, S. A Survey on False Alarm Reduction in Emergency Response Systems. IEEE Communications Surveys &
Tutorials. 2020; 22(3): 1850–1874.
5. Vaddepally, R. Architectural Optimization for Real-Time Edge Inference in Low-Power Mobile Devices. Advanced Computing Journal.
2026; 11(1): 45–58.
6. Reddy, V., & Rao, P. Phonetic Mapping of Dravidian Languages for Lightweight ASR Models. Indian Journal of Computer Science. 2025;
10(4): 202–215.
7. Peralta, G., et al. Energy-Efficient Acoustic Monitoring for Always-On Safety Applications. Journal of Systems Architecture. 2024; 146:
103042.
8. Anderson, L. Privacy-Preserving SOS Architectures: The Shift from Cloud to Edge. Cybersecurity Review. 2026; 9(2): 88–101.
9. Google Android Developers. Technical Whitepaper: Background Execution Limits and Foreground Service Types in Android 16.
Android Developer Portal. 2026.
10. IEEE Standard 1616.1-2025. Standard for Interoperability of Mobile SOS Systems with Public Safety Answering Points (PSAPs). IEEE
Standards Association. 2025.
11. Sharma, A., & Gupta, V. The Shift to Edge-NLP: Reducing Latency in Critical Human-Machine Interaction. ACM Transactions on
Embedded Computing. 2025; 24(1): 12–28.
12. Lopez, M. Cross-Linguistic Challenges in Localized Speech Recognition for Emerging Markets. International Journal of Bilingualism. 2025;
29(3): 315–330.
13. Vosk AI Open Source Initiative. Localized Weighted Finite-State Transducers (WFST) for Mobile Speech-to-Text. Vosk Research
Documentation. 2024.
14. [14]. Miller, J. T., & Thompson, S. Signal Processing for Robust Voice Triggering in High-Noise Urban Environments. IEEE Transactions
on Signal Processing. 2024; 72: 415–429
2. Koubaa, A., et al. A Service-Oriented Architecture for Critical IoT Applications. IEEE Access. 2018; 6: 1293–1305.
3. Debatin, N., et al. Evaluation of Offline Speech Recognition Engines for Embedded Systems. International Journal of Embedded Systems.
2021; 14(2): 110–118.
4. Chatterjee, S., & Misra, S. A Survey on False Alarm Reduction in Emergency Response Systems. IEEE Communications Surveys &
Tutorials. 2020; 22(3): 1850–1874.
5. Vaddepally, R. Architectural Optimization for Real-Time Edge Inference in Low-Power Mobile Devices. Advanced Computing Journal.
2026; 11(1): 45–58.
6. Reddy, V., & Rao, P. Phonetic Mapping of Dravidian Languages for Lightweight ASR Models. Indian Journal of Computer Science. 2025;
10(4): 202–215.
7. Peralta, G., et al. Energy-Efficient Acoustic Monitoring for Always-On Safety Applications. Journal of Systems Architecture. 2024; 146:
103042.
8. Anderson, L. Privacy-Preserving SOS Architectures: The Shift from Cloud to Edge. Cybersecurity Review. 2026; 9(2): 88–101.
9. Google Android Developers. Technical Whitepaper: Background Execution Limits and Foreground Service Types in Android 16.
Android Developer Portal. 2026.
10. IEEE Standard 1616.1-2025. Standard for Interoperability of Mobile SOS Systems with Public Safety Answering Points (PSAPs). IEEE
Standards Association. 2025.
11. Sharma, A., & Gupta, V. The Shift to Edge-NLP: Reducing Latency in Critical Human-Machine Interaction. ACM Transactions on
Embedded Computing. 2025; 24(1): 12–28.
12. Lopez, M. Cross-Linguistic Challenges in Localized Speech Recognition for Emerging Markets. International Journal of Bilingualism. 2025;
29(3): 315–330.
13. Vosk AI Open Source Initiative. Localized Weighted Finite-State Transducers (WFST) for Mobile Speech-to-Text. Vosk Research
Documentation. 2024.
14. [14]. Miller, J. T., & Thompson, S. Signal Processing for Robust Voice Triggering in High-Noise Urban Environments. IEEE Transactions
on Signal Processing. 2024; 72: 415–429
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