NDLI: Statistical Modeling and Retrieval of Polyphonic Music

Content Provider	IEEE Xplore Digital Library
Author	Unal, E. Georgiou, P.G. Narayanan, S.S. Chew, E.
Copyright Year	2007
Description	Author affiliation: Southern California Univ., Los Angeles (Unal, E.; Georgiou, P.G.; Narayanan, S.S.)
Abstract	In this article, we propose a solution to the problem of query by example for polyphonic music audio. We first present a generic mid-level representation for audio queries. Unlike previous efforts in the literature, the proposed representation is not dependent on the different spectral characteristics of different musical instruments and the accurate location of note onsets and offsets. This is achieved by first mapping the short term frequency spectrum of consecutive audio frames to the musical space (the spiral array) and defining a tonal identity with respect to center of effect that is generated by the spectral weights of the musical notes. We then use the resulting single dimensional text representations of the audio to create a-gram statistical sequence models to track the tonal characteristics and the behavior of the pieces. After performing appropriate smoothing, we build a collection of melodic n-gram models for testing. Using perplexity-based scoring, we test the likelihood of a sequence of lexical chords (an audio query) given each model in the database collection. Initial results show that, some variations of the input piece appears in the top 5 results 81% of the time for whole melody inputs within a 500 polyphonic melody database. We also tested the retrieval engine for small audio clips. Using 25s segments, variations of the input piece are among the top 5 results 75% of the time.
Starting Page	405
Ending Page	409
File Size	410712
Page Count	5
File Format	PDF
ISBN	9781424412747
DOI	10.1109/MMSP.2007.4412902
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-01
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Music information retrieval Testing Audio databases Laboratories Instruments Signal processing algorithms Multiple signal classification Hidden Markov models Spatial databases Speech analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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