The self-control training method of vocal performance teaching in a new media environment

Abstract Due to the diverse development trend of modern media, new media arts and applications are being presented in field vocal performance teaching with its many advantages interactivity, immediacy, sharing, comprehensiveness, versatility, community, personalization. In this paper, by decoding EEG signal, through process data pre-processing, feature extraction, identification, classification, calculating significance each element time-frequency matrix, an iso-dimensional mask matrix can be obtained. Then conditional random model is established on theory get parameters model. Finally, obtained maximizing following entropy function, which brought into Lagrangian operator obtain pairwise operator. signal decoded realize self-control training environment. The experimental results show that conducting intervention test insight, mean value total score 61.99±11.45, effect has stability. Therefore, improving self-control, forming correct expressions forms, enriching emotions important for performance.