Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
Creating music videos using automatic media analysis
Proceedings of the tenth ACM international conference on Multimedia
Discovering Musical Structure in Audio Recordings
ICMAI '02 Proceedings of the Second International Conference on Music and Artificial Intelligence
Automated extraction of music snippets
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Music thumbnailing via structural analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Content-based UEP: a new scheme for packet loss recovery in music streaming
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Content-based music structure analysis with applications to music semantics understanding
Proceedings of the 12th annual ACM international conference on Multimedia
Automatic singer identification
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
Labelling the Structural Parts of a Music Piece with Markov Models
Computer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music
Music structure analysis using a probabilistic fitness measure and a greedy search algorithm
IEEE Transactions on Audio, Speech, and Language Processing
Segmenting music through the joint estimation of keys, chords and structural boundaries
Proceedings of the 21st ACM international conference on Multimedia
Music Homogeneity Analysis through Instantaneous Frequencies
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Elastic Net subspace clustering applied to pop/rock music structure analysis
Pattern Recognition Letters
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Our proposed approach detects music structures by looking at beat space segmentation, chords, singing-voice boundaries, and melody- and content-based similarity regions. Experiments illustrate that the proposed approach is capable of extracting useful information for music applications.