Application of Big Data-based Information Technology in Business English Courses in Colleges and Universities

Abstract

Abstract In this paper, after using Cool Edit Pro2.1 software to complete the speech signal acquisition work, the DTW method is used to pre-emphasize the speech signal. Due to the small continuous correlation between adjacent frames, the use of windowing and frame-splitting operation makes the amplitude change of the speech signal smooth and obtains the spectral envelope of the speech signal. The negative impact of MFCC feature parameter extraction is optimized by parameterizing the volume intensity and fundamental trajectory, and the application of the English scoring mechanism in business English education is explored. According to the current situation of business English teaching in colleges and universities, research problems and sampling objects are identified, and statistical analysis is applied to analyze the teaching effect of business English informatization by example. The results show that the speech evaluation system of spoken business English based on DTW does not differ much from the similar results of the scoring of the master’s degree of English majors in our university, and its difference value always stays between 1 and 10. In terms of the simple correlation coefficient and significance level (0.01), the simple correlation coefficient between teaching effectiveness and the use of technological media is 0.385 (P=0.00), which means that there is a significant correlation between both teaching effectiveness and the use of technological media. This study improves the standardization of English pronunciation among students, which is important for the development of business English in colleges and universities.