Lingzhu Ji
In current English learning, listening, and speaking is an important part of English learning. To cultivate students’ Englishlistening and speaking ability and meet the demand for language communication improvement today, this paper uses bigdata technology as the main support to recognize, noise reduction and feature extraction of input speech using speechrecognition algorithm, noise elimination algorithm and feature extraction algorithm, respectively. Obtain data related tostudents’ English listening and speaking abilities to form systematic and complete student big data. Through pre-processing and mining, it provides a basis for decision making in English listening and speaking teaching. According tothe results of the analysis of students’ English listening and speaking ability, the percentage of students who liked Englishlistening very much in the pre-test was 25% of the class, and the percentage of students who thought they could beoptimistic about the hardships in learning was 18%. After practicing the improvement path, the percentages of studentsincreased to 38% and 29%, respectively. The mean value of listening at the pre-test was 20.23, which was lower than themean value of listening at the post-test, 21.72. The above experimental results are sufficient to show that the developmentof the pathway in this paper can make students more motivated and enthusiastic in learning English listening and speaking,and thus improve their English listening and speaking skills.
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