Design and Implementation of Embedded Real-Time English Speech Recognition System Based on Big Data Analysis

Abstract

This article uses Field Programmable Gate Array (FPGA) as a carrier and uses IP core to form a System on Programmable Chip (SOPC) English speech recognition system. The SOPC system uses a modular hardware system design method. Except for the independent development of the hardware acceleration module and its control module, the other modules are implemented by software or IP provided by Xilinx development tools. Hardware acceleration IP adopts a top-down design method, provides parallel operation of multiple operation components, and uses pipeline technology, which speeds up data operation, so that only one operation cycle is required to obtain an operation result. In terms of recognition algorithm, a more effective training algorithm is proposed, Genetic Continuous Hidden Markov Model (GA_CHMM), which uses genetic algorithm to directly train CHMM model. It is to find the optimal model by encoding the parameter values of the CHMM and performing operations such as selection, crossover, and mutation according to the fitness function. The optimal parameter value after decoding corresponds to the CHMM model, and then the English speech recognition is performed through the CHMM algorithm. This algorithm can save a lot of training time, thereby improving the recognition rate and speed. This paper studies the optimization of embedded system software. By studying the fixed-point software algorithm and the optimization of system storage space, the real-time response speed of the system has been reduced from about 10 seconds to an average of 220 milliseconds. Through the optimization of the CHMM algorithm, the real-time performance of the system is improved again, and the average time to complete the recognition is significantly shortened. At the same time, the system can achieve a recognition rate of over 90% when the English speech vocabulary is less than 200.

Implementation of Bioelectrical Impedance Measuring Instrument Based on Embedded System

“…The main aim of the present research is to make the system digital in the form of data storage and the transaction to the subjects whose measurements will be done. As a developed prototype used to measure the BI of the human body at multifrequency, it is necessary to send measured data to the subjects and examiner for future use or research the data academically or commercially [35][36][37][38][39][40]. The research uses an in-build device with a Wi-Fi chip to send the data to the server.…”

English Speech Recognition and Evaluation of Pronunciation Quality Using Deep Learning

“…The recognition of the English language is crucial in evaluating college English multimedia teaching [11,12]. It is the technique for automatically translating speech signals into corresponding objects or words using machine learning and artificial intelligence [13].…”

“…In problem-solving process of speech processing, the probability distribution of continuous observation is explained by HMM probability density function, in which the Gaussian mixture function is the probability density function with the widest application range as by equation (11).…”