Audio content-based feature extraction algorithms using J-DSP for arts, media and engineering courses

Mohit Shah, Gordon Wichern, Andreas Spanias, Harvey Thornburg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

J-DSP is a java-based object-oriented online programming environment developed at Arizona State University for education and research. This paper presents a collection of interactive Java modules for the purpose of introducing undergraduate and graduate students to feature extraction in music and audio signals. These tools enable online simulations of different algorithms that are being used in applications related to content-based audio classification and Music Information Retrieval (MIR). The simulation software is accompanied by a series of computer experiments and exercises that can be used to provide hands-on training. Specific functions that have been developed include modules used widely such as Pitch Detection, Tonality, Harmonicity, Spectral Centroid and the Mel-Frequency Cepstral Coefficients (MFCC). This effort is part of a combined research and curriculum program funded by NSF CCLI that aims towards exposing students to advanced multidisciplinary concepts and research in signal processing.

Original languageEnglish (US)
Title of host publication40th Annual Frontiers in Education Conference
Subtitle of host publicationCelebrating Forty Years of Innovation, FIE 2010 - Conference Program
PagesT1F1-T1F6
DOIs
StatePublished - Dec 1 2010
Event40th Annual Frontiers in Education Conference: Celebrating Forty Years of Innovation, FIE 2010 - Arlington, VA, United States
Duration: Oct 27 2010Oct 30 2010

Publication series

NameProceedings - Frontiers in Education Conference, FIE
ISSN (Print)1539-4565

Other

Other40th Annual Frontiers in Education Conference: Celebrating Forty Years of Innovation, FIE 2010
CountryUnited States
CityArlington, VA
Period10/27/1010/30/10

Keywords

  • Audio content search and classification
  • Digital signal processing
  • Feature extraction
  • Online education
  • Signals and systems education

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

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