Nonlinear distortions pose a serious problem for the quality preservation of audio and speech signals. In order to address this problem, such signals are processed by nonlinear models. Functional link adaptive filter (FLAF) is a linear-in-the-parameter nonlinear model, whose nonlinear transformation of the input is characterized by a basis function expansion, thus satisfying the universal approximation property. Since the expansion type affects the nonlinear modeling according to the nature of the input signal, in this paper we investigate the FLAF modeling performance involving the most popular functional expansions when audio and speech signals are processed. A comprehensive analysis is conducted in order to provide the best suitable solution for the processing of nonlinear audio signals. Experimental results are assessed also in terms of signal quality and intelligibility.

Functional Link Expansions for Nonlinear Modeling of Audio and Speech Signals / Comminiello, Danilo; Scardapane, Simone; Scarpiniti, Michele; Parisi, Raffaele; Uncini, Aurelio. - STAMPA. - (2015), pp. 1-8. (Intervento presentato al convegno 2015 International Joint Conference on Neural Networks tenutosi a Killarney, Ireland nel 12-17 Luglio) [10.1109/IJCNN.2015.7280443].

Functional Link Expansions for Nonlinear Modeling of Audio and Speech Signals

COMMINIELLO, DANILO;SCARDAPANE, SIMONE;SCARPINITI, MICHELE;PARISI, Raffaele;UNCINI, Aurelio
2015

Abstract

Nonlinear distortions pose a serious problem for the quality preservation of audio and speech signals. In order to address this problem, such signals are processed by nonlinear models. Functional link adaptive filter (FLAF) is a linear-in-the-parameter nonlinear model, whose nonlinear transformation of the input is characterized by a basis function expansion, thus satisfying the universal approximation property. Since the expansion type affects the nonlinear modeling according to the nature of the input signal, in this paper we investigate the FLAF modeling performance involving the most popular functional expansions when audio and speech signals are processed. A comprehensive analysis is conducted in order to provide the best suitable solution for the processing of nonlinear audio signals. Experimental results are assessed also in terms of signal quality and intelligibility.
2015
2015 International Joint Conference on Neural Networks
Functional link adaptive filters; nonlinear modeling; nonlinear acoustic echo cancellation; speech
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Functional Link Expansions for Nonlinear Modeling of Audio and Speech Signals / Comminiello, Danilo; Scardapane, Simone; Scarpiniti, Michele; Parisi, Raffaele; Uncini, Aurelio. - STAMPA. - (2015), pp. 1-8. (Intervento presentato al convegno 2015 International Joint Conference on Neural Networks tenutosi a Killarney, Ireland nel 12-17 Luglio) [10.1109/IJCNN.2015.7280443].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/797358
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