NDLI: Chirplet representation for audio signals based on model order selection criteria

Content Provider	IEEE Xplore Digital Library
Author	Mowlaee, P. Saber, H. Amid, A.
Copyright Year	2009
Description	Author affiliation: School of ECE, College of Engineering, University of Tehran, Iran (Saber, H.) \|\| Amirkabir University of Technology, Tehran, Iran (Mowlaee, P.) \|\| Azad University, Tehran south Branch, Iran (Amid, A.)
Abstract	In many signal processing applications including Audio and speech processing as well as other research areas of diagnosis of failures in rotating machinery, finding a compact representation of observations signals is often highly desirable. In this respect, chirplets have recently been introduced as an efficient tool for signal representation. However, determining the required number of chirp atoms for the perfect estimation of an observed signal is of great importance. In this research work we study the chirplets signal decomposition to find a compact representation for audio signals of music and speech. The number of chirplets to be used is determined by using the state-of-the-art information criteria. Simulation and experimental results show that by using 4 chirplets are enough for accurate signal representation of music while about 7 to 9 chirplets suffices for speech signal reconstruction. As another application the evaluations are also made on vibration signals. Finally, extracted chirplet toms are employed to reconstruct the observed signals of music and speech. Subjective tests show acceptable results for signal reconstruction.
Starting Page	927
Ending Page	934
File Size	1033244
Page Count	8
File Format	PDF
ISBN	9781424438075
DOI	10.1109/AICCSA.2009.5069443
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-10
Publisher Place	Morocco
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chirp Multiple signal classification Signal processing Signal representations Signal reconstruction Speech processing Machinery Signal resolution Data mining Testing
Content Type	Text
Resource Type	Article

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