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Signal-Driven Window-Length Adaptation for Sinusoid Detection in Polyphonic Music

DSpace at IIT Bombay

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Title Signal-Driven Window-Length Adaptation for Sinusoid Detection in Polyphonic Music
 
Creator RAO, V
GADDIPATI, P
RAO, P
 
Subject Signal sparsity
sinusoid detection
window adaptation
FREQUENCY
AUDIO
VOCODER
 
Description Audio processing applications that use short-time signal analysis techniques typically utilize fixed window duration single-or multi-resolution analyses. However, different real-world signal conditions such as polyphony and non-stationarity, manifested as musical accompaniment and pitch-modulations, respectively, in the context of music content analysis, require varying data window lengths for reliable processing. In this paper, we investigate the use of signal sparsity for adapting analysis window lengths. Adaptive-window analysis driven by different measures of sparsity applied to the local spectrum, such as kurtosis and Gini index, is evaluated and shown to be superior to fixed-window analysis in terms of sinusoid detection and frequency estimation for simulated and real signals. A window main-lobe matching method for sinusoid detection is also shown to be more robust to signal conditions such as polyphony and frequency modulation relative to other methods.
 
Publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
 
Date 2014-10-15T12:02:54Z
2014-10-15T12:02:54Z
2012
 
Type Article
 
Identifier IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 20(1)342-348
http://dx.doi.org/10.1109/TASL.2011.2162319
http://dspace.library.iitb.ac.in/jspui/handle/100/14855
 
Language en