The invention discloses a music similarity detection method based on mixed characteristics and a
Gaussian mixed model. According to the basic thought, the method comprises the steps of using a gamma-tone
cepstrum coefficient for conducting similarity detection, and using weighting similarities of various characteristics as a final detection result; providing a
modulation spectrum characteristic based on a frame shaft, using the characteristic for representing a music long-time characteristic, and using the combination of the long-time characteristic and a short-time characteristic as the input of modeling in the next step; using the
Gaussian mixed model for conducting modeling on the music characteristics, firstly, utilizing a dynamic K mean value method for conducting initialization on the model, then, using an expectation-maximization
algorithm for conducting model training, obtaining accurate
model parameters, and finally using a log-likelihood ratio
algorithm for obtaining the similarities between the pieces of music. According to the music similarity detection method, the obtaining of the music characteristics is more sufficient and thorough, the accuracy degree of music recommendation is improved, the characteristic vector dimensionality can be reduced, the information memory content of a music
database is reduced, and the accuracy degree of the music recommendation is improved.