SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
MUSEMBLE: A novel music retrieval system with automatic voice query transcription and reformulation
Journal of Systems and Software
An efficient approach to extracting approximate repeating patterns in music databases
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Searching Musical Audio Using Symbolic Queries
IEEE Transactions on Audio, Speech, and Language Processing
Challenging Uncertainty in Query by Humming Systems: A Fingerprinting Approach
IEEE Transactions on Audio, Speech, and Language Processing
Discovering nontrivial repeating patterns in music data
IEEE Transactions on Multimedia
An effective music information retrieval method using three-dimensional continuous DP
IEEE Transactions on Multimedia
Factors affecting music retrieval in query-by-melody
IEEE Transactions on Multimedia
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With the explosive growth of digital music content-based music information retrieval especially query by humming/singing have been attracting more and more attention and are becoming popular research topics over the past decade. Although query by humming/singing can provide natural and intuitive way to search music, retrieval system still confronts many issues such as key modulation, tempo change, note insertion, deletion or substitution which are caused by users and query transcription respectively. In this paper, we propose a novel approach based on fault tolerance and recursive segmentation to solve above problems. Music melodies in database are represented with specified manner and indexed using inverted index method. Query melody is segmented into phrases recursively with musical dictionary firstly. Then improved edit distance, pitch deviation and overall bias are employed to measure the similarity between phrases and indexed entries. Experimental results reveal that proposed approach can achieve high recall for music retrieval.