Audio Content-Based Feature Extraction Algorithms Using J-DSP for Arts, Media and Engineering Courses

被引：0

作者：

Shah, Mohit ^{[1
]}

Wichern, Gordon ^{[1
]}

Spanias, Andreas ^{[1
]}

Thornburg, Harvey ^{[1
]}

机构：

[1] Arizona State Univ, Sch ECEE, SenSIP Ctr, Tempe, AZ 85287 USA

来源：

2010 IEEE FRONTIERS IN EDUCATION CONFERENCE (FIE) | 2010年

关键词：

audio content search and classification; digital signal processing; feature extraction; online education; signals and systems education; RETRIEVAL;

D O I：

暂无

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

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.

引用

页数：6

共 20 条

[1] Audio content-based feature extraction algorithms using J-DSP for arts, media and engineering courses
School of ECEE, SenSIP Center, Arizona State University, United States
Proc. Front. Educ. Conf. FIE, (T1F1-T1F6):
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