Users need a system that can not only satisfy the natural habit of listening to songs and recognizing songs but also improve the feedback and effect of retrieval. The traditional music retrieval method is to match the song names or lyrics in the music retrieval library according to the entered keywords by the user, which is no longer in line with the needs of modern users.
Therefore, the research on MIR (music information retrieval) has been widely concerned by academic circles. Although people are born with the ability to appreciate and identify music, it is very difficult for computers to analyze, understand, and retrieve music content. This method not only improves the recall rate of the fundamental frequency of the human voice but also improves the recall rate and pitch accuracy rate of the whole main melody extraction system.Īs an effective carrier to express and convey emotions, the study of music is closer to people's lives. Meanwhile, the recall rate of the algorithm can reach about 95%. The experimental results show that the lowest octave error of this method is 1.46. In this article, more features are used to distinguish the pitch contour of vocal fundamental frequency from that of the nonvocal fundamental frequency, which does not only depend on energy or a certain feature. In addition, in order to avoid the sharp jump of the estimated melody pitch in the same note duration range, this article proposes a main melody extraction method combining the SVM algorithm with dynamic programming. Thereafter, the multi-resolution short-time Fourier transform suitable for processing song signals is introduced. In the part of multi-fundamental frequency extraction, this article first filters the song signal with equal loudness and weakens the energy of the high-frequency and low-frequency parts of the song signal.
In this article, the SVM algorithm is used to analyze and discuss music melody extraction and multi-pitch estimation. Main melody extraction and multi-pitch estimation are two important research topics in the MIR field.
0 kommentar(er)
