Paper Info
Title
Automatic Music Summarization Based On Music Structure Analysis
Abstract
In this paper, we present a novel approach for music summarization based on music structure analysis. From the audio signal, we first extract the note onset representing the time tempo of the song and the music structure analysis can be performed based on this tempo information. After music content has been structured into different semantic regions such as Introduction (Intro), Verse, Chorus, Ending (Outro), etc., the final music summary can be created with chorus and music phrases which are included anterior or posterior to selected chorus to get the desired length of the final summary. In this way, we can guarantee that the summaries begin and end at meaningful music phrase boundaries, which is a difficult problem for existing music summarization methods. Experiments show our proposed method can capture the main theme of the music compared to the ideal summaries selected by music experts and user subjective evaluation indicates our proposed method has a good performance.
Year
DOI
Venue
2005
10.1109/ICASSP.2005.1415618
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING
Keywords
Field
DocType
chorus,indexing,information analysis,multiple signal classification,audio signal processing,feature extraction,structure analysis,rhythm,machine learning,music,frequency,pattern matching,data mining,signal analysis
Audio signal,Computer science,Phrase,Search engine indexing,Natural language processing,Artificial intelligence,Audio signal processing,Chorus,Automatic summarization,Pattern recognition,Speech recognition,Pop music automation,Rhythm
Conference
ISSN
Citations 
PageRank 
1520-6149
2
0.44
References 
Authors
7
4
Name
Order
Citations
PageRank
Xi Shao122619.08
Namunu C. Maddage234526.51
Changsheng Xu34957332.87
Mohan Kankanhalli43825299.56