MUSIC CLASSIFICATION DEVICE USING AUTOREGRESSIVE MODEL AND METHOD THEREOF

摘要

The present invention relates to a music classification device using an autoregressive model and a method thereof. The music classification device comprises: an input portion for receiving a sound source; a short-term feature extracting portion for extracting a short-term feature vector for a tone feature of the sound source inputted from the input portion; a long-term feature extracting portion for extracting a long-term feature vector by using the short-term feature vector; an AR modeling portion for extracting an LPC by using the extracted short-term feature vector, modeling the extracted LPC in the autoregressive model, producing a new feature vector having an increased degree, and converting the same into an LSP parameter; a feature selection portion for selecting a top feature vector having a high recognition rate among the short-term feature vector, the long-term feature vector, and the new feature vector; a model generation portion for producing a classification model of a music by using the selected feature vector; and a music classification portion for classifying a genre or a mode of a test music inputted based on the classification model. According to the present invention, through a selection process of the top feature vector after extracting the feature vector of the music, the music classification device using an autoregressive model enables to reduce time required to get a classification result and to get the high recognition rate by enabling to reduce the calculation amount required for a genre classification of inputted music data.