Research on the Reform of Art Education and Teaching based on the Background of Big Data

Abstract

In order to improve the quality of art education and teaching reform, this paper combines big data technology to carry out research on art education reform and improve the effect of art education reform. This paper introduces an improved multiband spectral subtraction method for amplitude spectral enhancement of speech by a log-MMSE estimator. The experimental results show that the algorithm can effectively reduce the "music noise" problem of traditional spectral subtraction, and reduce the distortion problem of the art teacher's dialogue speech. Moreover, the enhanced dialogue speech signal obtained by the improved multi-band spectral subtraction in this paper can extract more time-domain features of the speech signal than the traditional spectral subtraction method. Through experimental research, it can be seen that the art education model proposed in this paper can effectively improve the effect of modern art teaching and improve the teaching interaction between teachers and students.