In order to improve the effect of music classroom teaching and the degree of informatization, this paper builds a music classroom auxiliary teaching system with the support of intelligent speech recognition technology, and conducts in-depth research on the audio classification and segmentation technology of music teaching classrooms. Moreover, this paper uses support vector machines to divide audio into five types: mute, background sound, song music, speech, and noisy speech. At the same time, this paper also proposes a smoothing method based on the classification result sequence to obtain audio segmentation points. In addition, this paper constructs a system model based on the actual needs of music classroom teaching, and performs vocal feature recognition with the support of intelligent speech recognition. Finally, this paper verifies and analyzes the performance of the system constructed in this paper through experimental research. The research results show that the intelligent music classroom auxiliary teaching system constructed in this paper has a certain effect.
Enlightenment on Vocal Music Classroom Teaching from the Perspective of Big Data