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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/3664

Title: Efficient Acoustic Feature Computation Using FPGAs
Authors: Schmidt, Erik M.
Speck, Jacquelin A.
Keywords: acoustics;FPGA;music information retrieval
Issue Date: 15-Apr-2010
Series/Report no.: Research Day Category: Physical Science and Engineering
Abstract: Many recent advances in music information retrieval (MIR) have been data-driven. Widespread performance evaluations on common data sets, like the annual MIREX events, have been instrumental in advancing the field. Such endeavors incur large computational costs and could potentially benefit from faster calculation of acoustic features. Traditional cluster-based solutions are expensive and space- and power inefficient. The massively parallel architecture of the field programmable gate array (FPGA) makes it possible to design lower-cost, applicationspecific chips rivaling cluster speed for large-scale acoustic feature computation. Such devices also show potential for implementations of MIR systems on embedded devices where hardware acceleration is a necessity. We present a prototype Xilinx System Generator (XSG) library for acoustic feature calculation. We use a genre classification task to compare the performance of simulated hardware features to those computed using standard methods. Finally, we discuss ongoing efforts toward a working hardware design.
Description: Student Author: Erik M. Schmidt, College of Engineering, ECE; Student Author: Jacquelin A. Speck, College of Engineering, ECE; Adviser: Dr. Youngmoo Kim, College of Engineering, ECE
URI: http://hdl.handle.net/1860/3664
Appears in Collections: Research Day Posters (COE)

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