This paper proposes a feature extraction method for waveform music files based on their complex and changeable signals.First, we denoise the music signals in the time domain.The signal envelope is got by the Gaussian low-pass filter for the high frequency signals.And we use FFT algorithm in frequency domain on the peak detection to extract the notes and the feature.Based on the strength laws of the notes in the bars, we extract bars and bars eigenvector by using the window moving match algorithm, and then mark off the period according to the similarity between bars, and get period feature with emotional factors.The period feature is input into RAN neural network emotion recognizer for emotion recognition of certain periods, and to decide the emotion feature of the whole music.The experimental results show that this method is effective in extracting features of different types of music.
SHI Xiang-bin, SUN Peng-yu
. Research on a method of feature extraction for waveform music files[J]. Journal of Shenyang Aerospace University, 2013
, 30(5)
: 60
-66
.
DOI: 10.3969/j.issn.2095-1248.2013.05.013
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