A Framework for Smart Home System with Voice Control Using NLP Methods

The proliferation of information technologies and the emergence of ubiquitous computing have quickly transformed electronic devices from isolated islands of data and control into interconnected parts of intelligent systems. These network-based systems have advanced features, including Internet of Things (IoT) sensors and actuators, multiple connectivity options and multimodal user interfaces, and they also enable remote monitoring and management. In order to develop a human machine interface of smart home systems with speech recognition, we propose a new IoT-fog-cloud framework using natural language processing (NLP) methods. The new methodology adds utterance to command transformation to the existing cloud-based speech-to-text and text-to-speech services. This approach is flexible and can be easily adapted for different types of automation systems and consumer electronics as well as to almost every non-tonal language not currently supported by online platforms for intent detection and classification. The proposed framework has been employed in the development of prototypes of voice user interface extension of existing smart security system via new service for speech intent recognition. Tests on the system were carried out and the obtained results show the effectiveness of the new voice communication option. The speech-based interface is reliable; it facilitates customers and improves their experience with smart home devices.

Automated summary

The rapid development of information technology and ubiquitous computing has transformed electronic devices from isolated islands of data and control to interconnected parts of intelligent systems. These network-based systems have advanced features, including IoT sensors and actuators, multiple connectivity options, and multimodal user interfaces, enabling remote monitoring and management. To develop a smart home system human machine interface with speech recognition, a new IoT-fog-cloud framework using natural language processing (NLP) methods is proposed. The framework adds utterance to command transformation to existing cloud-based speech-to-text and text-to-speech services, providing flexibility for different automation systems and languages.