This paper provides the design, implementation, and experimental assessment of an offline bilingual Arabic-English voice-controlled smart home automation system based on embedded hardware and radio-frequency (RF) communication. The given system uses an Arduino-based master-slave architecture, in which local speech recognition is realized with the help of the Elechouse Voice Recognition Module V3, and control commands being sent via HC-12 RF modules with 433 MHz frequency. In contrast to cloud-based voice assistants, all speech processing goes locally, which means that the user privacy is guaranteed and low-latency response is also provided. The system is capable of Arabic and English voice recognition and operating domestic appliances using optocoupler-isolated relay circuits. The experimental performance of RF communication in indoor settings has shown stable communications up to a range of 60m, end to end response latency of less than 300ms and command recognition accuracy of between 85 and 95 percent per command, and a total average command recognition accuracy of 90 percent under low noise conditions. Under high ambient noise, the performance is degraded, which demonstrates the weakness of template-based speech recognition. The findings suggest that offline bilingual voice interfaces used with low-power RF communication can offer a viable, privacy-sensitive solution to small-scale automation of the smart home as well as a platform upon which noise-resistant on-device learning algorithms will be implemented in future applications.
Talal et al. (Sun,) studied this question.
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