Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Evaluation of a simple and effective music information retrieval method
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchical filtering method for content-based music retrieval via acoustic input
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
HMM-based musical query retrieval
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
A comparison of melodic database retrieval techniques using sung queries
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A statistical approach to retrieval under user-dependent uncertainty in query-by-humming systems
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
The MUSART Testbed for Query-by-Humming Evaluation
Computer Music Journal
Music retrieval: a tutorial and review
Foundations and Trends in Information Retrieval
Compacting music signatures for efficient music retrieval
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
An Approximate String Matching Algorithm for Content-Based Music Data Retrieval
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
SIRC: An Extensible Reconfigurable Computing Communication API
FCCM '10 Proceedings of the 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines
Note segmentation and quantization for music information retrieval
IEEE Transactions on Audio, Speech, and Language Processing
MIN-MAX: A Counter-Based Algorithm for Regular Expression Matching
IEEE Transactions on Parallel and Distributed Systems
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We propose an FPGA-based high performance parallel architecture for music retrieval through singing. The database consists of monophonic MIDI files which are modeled into strings, and the user sung query is modeled as a set of regular expressions (regexp), with consideration of possible key transpositions and tempo variations to tolerate imperfectly sung queries. An approximate regexp matching algorithm is developed to calculate the similarity between a regexp and a string, using edit distance as the metrics. The algorithm supports user sung queries starting anywhere in the database song, not necessarily from the beginning. Using the proposed formal models and algorithms, the similarity between the user sung query and each song in the database can be evaluated and the top-10 most similar results will be reported. We designed the approximate regexp matching algorithm in such way that all terms of the regexp can execute concurrently, which perfectly fits the massive parallelism provided by FPGA. The FPGA implemented melody matching engine (MME) is a parameterized modular architecture that can be reconfigured to implement different regexps by simply updating their parameter registers, and can therefore avoid the time-consuming code re-synthesis. MME also includes an on-board DDR2 memory to store the database, so that they can be read in to calculate edit distances locally on the board. This way, each MME forms a self-contained system and multiple MMEs can be clustered to increase parallel processing power, with virtually no overhead. MME is evaluated using the query corpus of ThinkIT with 355 sung files and database of 5563 MIDI files. It achieves a top-10 hit rate of 90.7% and a runtime of 19.4 seconds, averaging 54.6 milliseconds for a single query. MME achieves significant speedup over software-based systems while providing the same level of flexibility.