Analysis of the improvement path of English listening and speaking ability based on big data technology

In current English learning, listening, and speaking is an important part of English learning. To cultivate students' English listening and speaking ability and meet the demand for language communication improvement today, this paper uses big data technology as the main support to recognize, noise reduction and feature extraction of input speech using speech recognition algorithm, noise elimination algorithm and feature extraction algorithm, respectively. Obtain data related to students' English listening and speaking abilities to form systematic and complete student big data. Through preprocessing and mining, it provides a basis for decision making in English listening and speaking teaching. According to the results of the analysis of students' English listening and speaking ability, the percentage of students who liked English listening very much in the pre-test was 25% of the class, and the percentage of students who thought they could be optimistic about the hardships in learning was 18%. After practicing the improvement path, the percentages of students increased to 38% and 29%, respectively. The mean value of listening at the pre-test was 20.23, which was lower than the mean value of listening at the post-test, 21.72. The above experimental results are sufficient to show that the development of 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.