Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Towards the digital music library: tune retrieval from acoustic input
Proceedings of the first ACM international conference on Digital libraries
A tool for content based navigation of music
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Musical content-based retrieval: an overview of the Melodiscov approach and system
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Tune Retrieval in the Multimedia Library
Multimedia Tools and Applications
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Creating data resources for designing user-centric frontends for query by humming systems
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
Music retrieval: a tutorial and review
Foundations and Trends in Information Retrieval
Music copyright protection system using fuzzy similarity measure for music phoneme segmentation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Similarity clustering of music files according to user preference
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
User specific training of a music search engine
MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction
An FPGA based parallel architecture for music melody matching
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Hi-index | 0.01 |
Robustly addressing uncertainty in query formulation and search is one of the most challenging problems in multimedia information retrieval (MIR) systems. In this paper, a statistical approach to the problem of retrieval under the effect of uncertainty in Query by Humming (QBH) systems is presented. Direct transcription of audio to pitch and duration symbols is performed. From the transcribed data vector, finger prints that carry a fixed length of information from characteristic local points of the hummed melody are extracted. Instead of employing the humming input as a whole, extracted characteristic information packages are used for search through the database. The distance for each finger print to the original melodies in the database is calculated and converted to probabilistic similarity measures. Melodies with the highest similarity measures are returned to the user as the most likely query result. This algorithm is tested with manually annotated data comprising 250 humming samples in conjunction with a database of 200 pre-processed midi files. Retrieval accuracy of 94 percent is demonstrated for the samples of subjects that have some musical training/background compared to 72 percent accuracy achieved for the samples of non-trained subjects. Results also show that extracting finger prints with respect to characteristic local points of the hummed tune is an effective and robust way for search and retrieval under the effect of uncertainty