Fundamentals of speech recognition
Fundamentals of speech recognition
Digital Image Processing
Automated extraction of music snippets
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Music summarization using key phrases
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Discovering nontrivial repeating patterns in music data
IEEE Transactions on Multimedia
Music structure analysis by finding repeated parts
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
Similarity matrix processing for music structure analysis
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
Using duration models to reduce fragmentation in audio segmentation
Machine Learning
Towards structural analysis of audio recordings in the presence of musical variations
EURASIP Journal on Applied Signal Processing
True suffix tree approach for discovering non-trivial repeating patterns in a music object
Multimedia Tools and Applications
Music information retrieval using social tags and audio
IEEE Transactions on Multimedia - Special section on communities and media computing
Efficient sparse self-similarity matrix construction for repeating sequence detection
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A tree-construction search approach for multivariate time series motifs discovery
Pattern Recognition Letters
Repeating pattern discovery from audio stream
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Structural and semantic modeling of audio for content-based querying and browsing
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Music segmentation and summarization based on self-similarity matrix
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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Music and songs usually have repeating patterns and prominent structure. The automatic extraction of such repeating patterns and structure is useful for further music summarization, indexing and retrieval. In this paper, an effective approach of repeating pattern discovery and structure analysis of acoustic music data is proposed. In order to represent the melody similarity more accurately, in our approach, Constant Q transform is utilized in feature extraction and a novel similarity measure between musical features is proposed. From the self-similarity matrix of the music, an adaptive method is then presented to extract all significant repeating patterns. Based on the obtained repetitions, musical structure is further analyzed using a few heuristic rules. Finally, an optimization-based approach is proposed to determine the accurate boundary of each musical section. Evaluations on various music pieces indicate our approach is promising.