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
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Creator |
RAO, V
GADDIPATI, P RAO, P |
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Subject |
Signal sparsity
sinusoid detection window adaptation FREQUENCY AUDIO VOCODER |
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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.
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Publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Date |
2014-10-15T12:02:54Z
2014-10-15T12:02:54Z 2012 |
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Type |
Article
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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 |
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Language |
en
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