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Elimination of clicks from archive speech signals using sparse autoregressive modeling

Abstract

This paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear prediction, the factorized model is converted intoa generic sparse form in order to perform a projection-basedsignal interpolation. It is shown that the proposed algorithmis able to deal favorably with speech signals with strong glottalactivity, which is a serious problem for algorithms basedon the classical AR modeling.

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Category:
Conference activity
Type:
materiały konferencyjne indeksowane w Web of Science
Title of issue:
The 20th European Signal Processing Conference EUSIPCO 2012, Bukarest, 27-31 August 2012
Language:
English
Publication year:
2012
Bibliographic description:
Niedźwiecki M., Ciołek M..: Elimination of clicks from archive speech signals using sparse autoregressive modeling, W: The 20th European Signal Processing Conference EUSIPCO 2012, Bukarest, 27-31 August 2012, 2012, ,.
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Gdańsk University of Technology

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