Visualizing music and audio using self-similarity
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
The Spiral Array: An Algorithm for Determining Key Boundaries
ICMAI '02 Proceedings of the Second International Conference on Music and Artificial Intelligence
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Music summarization using key phrases
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Towards user-adaptive structuring and organization of music collections
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
Automatic synchronization between audio and partial music score representation
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
"The way it Sounds": timbre models for analysis and retrieval of music signals
IEEE Transactions on Multimedia
Audio chord labeling by musiological modeling and beat-synchronization
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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A variety of approaches exist to the automatic retrieval of the key part within a musical piece - its thumbnail. Most of these however do not use adequate modeling with respect to either harmony or rhythm. In this work we therefore introduce thumbnailing that aims at adequate musical feature modeling. The rhythmic structure is extracted to obtain a segmentation based on beats and bars by an IIR comb-filter bank. Further, we extract chroma energy distribution normalized statistics features of the segmented song improving performance with dB(A) and pitch correction. Harmonic similarities are determined by construction and analysis of a similarity matrix based on the normalized scalar product of the feature vectors. Last, thumbnails are found lending techniques from image processing. Extensive test runs on roughly 24 h of music reveal the high effectiveness of our approach.