The Effectiveness of College Chorus Conducting Teaching Innovation Based on Statistical Model Chorus Melody Recognition Algorithm in the New Media Environment

College education has gradually become one of the objects that our country attaches great importance to. Chorus teaching itself has strong practical characteristics, which requires teachers to change their original ideas, constantly explore new teaching methods, and combine theory and practice as much as possible, so that music majors can develop in an all-round way in conducting. Compared with the traditional non-statistical algorithm, the algorithm proposed in this paper borrows the statistical framework and model in continuous speech recognition, and has better robustness. In terms of acoustic model, high-order cepstral coefficients are used as features to avoid the negative impact of turbidity judgment and fundamental frequency estimation errors on system performance. At the same time, a key-independent quaternion model is trained to reflect the musical prior knowledge. The melody recognition result is finally obtained by the Viterbi decoding algorithm. Experiments show that the proposed algorithm has the best robustness under noisy conditions, while the performance on clean data is close to the best results among all the compared systems. On the basis of expounding the current situation of chorus conducting teaching in colleges and universities, this paper analyzes the innovative ideas of choral conducting teaching in the new media environment, in order to provide a reference for the teaching mode of choral conducting in colleges and universities.