It is well known that the production of speech involves non linear phenomena. Classical algorithms of speech analysis, nevertheless, are based on the assumption that speech is generated by a linear system. In this paper we will describe how, using signal prediction based on a quadratic Volterra operator, the classical linear techniques can be extended to include non-linear modeling of speech. An adaptive algorithm will de described. Application of this novel analysis approach in speech coding will be described and compared with the classical linear approaches. It will be shown that the non-linear approach yields better performances with respect to the linear one and therefore it is of interest for telecommunication application
This thesis investigated the potential use of Linear Predictive Coding in speech communication appli...
The aim of this paper is to provide an overview of Sparse Linear Prediction, a set of speech process...
A novel coding technique is presented for signal prediction with applications including speech codin...
Recent studies have shown that the airflow in the vocal tract is highly unstable and oscillates betw...
The analysis of speech is usually based on linear models. In this contribution speech features are t...
Linear predictive coding is probably the most frequently used technique in speech signal processing....
Non-linear prediction can be based on Volterra series expansion with some benefits especially when t...
The linear prediction coding of speech is based in the assumption that the generation model is auto...
A novel linearised Recursive Least Squares (LRLS) learning algorithm is presented for an adaptive no...
The filter involving the adaptation scheme of Volterra Series Least Mean Square(VSLMS) algorithm is ...
This report gives an overview of the speech coding system based on adaptive differential pulse-code-...
From the early pulse code modulation-based coders to some of the recent multi-rate wideband speech c...
In this paper we propose a Non-Linear Predictive Vector quantizer (PVQ) for speech coding, based on ...
Abstract: In this paper we describe a neural network for the nonlinear adaptive prediction of non-st...
Analysis of speech signals can be performed with the aid of linear or nonlinear statistics using app...
This thesis investigated the potential use of Linear Predictive Coding in speech communication appli...
The aim of this paper is to provide an overview of Sparse Linear Prediction, a set of speech process...
A novel coding technique is presented for signal prediction with applications including speech codin...
Recent studies have shown that the airflow in the vocal tract is highly unstable and oscillates betw...
The analysis of speech is usually based on linear models. In this contribution speech features are t...
Linear predictive coding is probably the most frequently used technique in speech signal processing....
Non-linear prediction can be based on Volterra series expansion with some benefits especially when t...
The linear prediction coding of speech is based in the assumption that the generation model is auto...
A novel linearised Recursive Least Squares (LRLS) learning algorithm is presented for an adaptive no...
The filter involving the adaptation scheme of Volterra Series Least Mean Square(VSLMS) algorithm is ...
This report gives an overview of the speech coding system based on adaptive differential pulse-code-...
From the early pulse code modulation-based coders to some of the recent multi-rate wideband speech c...
In this paper we propose a Non-Linear Predictive Vector quantizer (PVQ) for speech coding, based on ...
Abstract: In this paper we describe a neural network for the nonlinear adaptive prediction of non-st...
Analysis of speech signals can be performed with the aid of linear or nonlinear statistics using app...
This thesis investigated the potential use of Linear Predictive Coding in speech communication appli...
The aim of this paper is to provide an overview of Sparse Linear Prediction, a set of speech process...
A novel coding technique is presented for signal prediction with applications including speech codin...