Unit middleware for implementation of human–machine interconnection intelligent ecology construction

Abstract

General speech recognition models require large capacity and strong computing power. Based on small capacity and low computing power to realize speech analysis and semantic recognition is a research area with great challenges for constructing intelligent ecology of the Internet of Things. For this purpose, we set up the unit middleware for the implementation of human–machine interconnection, namely human–machine interaction based on phonetics and semantics control for constructing intelligent ecology of the Internet of Things. First, through calculation, theoretical derivation and verification we present a kind of novel deep hybrid intelligent algorithm, which has realized speech analysis and semantic recognition. Second, it is to establish unit middleware using the embedded chip as the core on the motherboard. Third, it is to develop the important auxiliary tools writer-burner and cross-compiler. Fourth, it is to prune procedures and system, download, burn and write the algorithms and codes into the unit middleware and cross-compile. Fifth, it is to expand the functions of the motherboard, provide more components and interfaces, for example including RFID(Radio Frequency Identification, RFID), ZigBee, Wi-Fi, GPRS(General Packet Radio Services, GPRS), RS-232 serial port, USB(Universal Serial Bus, USB) interfaces and so on. Sixth, we take advantage of algorithms, software and hardware to make machines "understand" human speech and "think" and "comprehend" human intentions so as to implement human–machine interconnection, which further structure the intelligent ecology of the Internet of Things. At last, the experimental results denote that the unit middleware have very good effect, fast recognition speed, high accuracy and good stability, consequently realizing the intelligent ecology construction of the Internet of Things.