Digital Music Waveform Analysis and Retrieval Based on Feature Extraction Algorithm
Author(s) -
Yang Jiao
Publication year - 2021
Publication title -
advances in multimedia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.278
H-Index - 17
eISSN - 1687-5699
pISSN - 1687-5680
DOI - 10.1155/2021/7131992
Subject(s) - waveform , computer science , digital audio , feature extraction , feature (linguistics) , artificial intelligence , music information retrieval , pattern recognition (psychology) , speech recognition , audio signal , speech coding , telecommunications , art , musical , radar , linguistics , philosophy , visual arts
In order to improve the feature extraction effect of digital music and improve the efficiency of music retrieval, this paper combines digital technology to analyze music waveforms, extract music features, and realize digital processing of music features. Taking the extraction of waveform music file features as the starting point, this paper combines the digital music feature extraction algorithm to build a music feature extraction model and conducts an in-depth analysis of the digital music waveform extraction process. In addition, by setting the threshold, the linear difference between the sampling points on both sides of the threshold on the leading edge of the waveform is used to obtain the overthreshold time. From the experimental research results, it can be seen that the music feature extraction model based on digital music waveform analysis proposed in this paper has good results.
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