In this work, we are concerned by a new iterative Kalman filtering scheme where a linear predictor model parameters are estimated from noisy speech. However, when only noise-corrupted speech is available, the enhancement performance of the Kalman filter is somewhat dependent on the accuracy of the linear prediction coefficients (LPCs) and excitation variance estimates. Nevertheless, linear pred...

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fi...

Speech coding algorithms based on Algebraic Code Excited Linear Prediction (ACELP) quantize and code the residual signal with a fixed algebraic codebook. This paper generalizes the conventional encoding to provide optimal bit consumption for all codebook designs by enumerating all possible states. The codebook designed is aimed for constant bit-rate applications applied on mobile devices.

This paper addresses the performance of various statistical data fusion techniques for combining the complementary score information in speaker verification. The complementary verification scores are based on the static and delta cepstral features. Both LPCC (Linear prediction-based cepstral coefficients) and MFCC (mel-frequency cepstral coefficients) are considered in the study. The experiment...

A high fidelity simulation is preferred for its remarkable accuracy for engineering problems. However, it requires long computational time, which leads to significant overhead and eventually hinders its application to design study. To overcome such impediments, a reduced-order method is utilized. Reducedorder method can effectively represent a simulation output as a linear combination of a basi...

This paper examines schemes that modify linear prediction (LP) analysis for speech signals. First, techniques which improve the conditioning of the LP equations are examined. White noise compensation for the correlations is justified from the point of view of reducing the range of values which the predictor coefficients take on. The efficacy of the procedure is measured over a large speech data...

This paper proposes a novel parametric representation of mandarin intonation based on orthogonal polynomial approximation. The polynomial is a simplified representation of Parallel Encoding and Target Approximation (PENTA) intonation model that includes a target component and an approximation component. We also propose predicting the polynomial parameters from linguistic and phonetic attributes...

This Paper discusses the usefullness of the residual signal for speaker recognition. It is shown that the combination of both a measure defined over LPCC coefficients and a measure deffined over the energy of the residual signal gives rise to an improvement over the classical method which considers only the LPCC coefficients. If the residual signal is obtained from a linear prediction analisys,...

To establish the estimation models, the linear regression technique is used to analyze the historical data. This technique is also applied in combination with logarithm transformation of the collected data. Our results show that the correlation coefficients (or R) between size (FFP) and real effort and size (FFP) and cost are 89% and 88% respectively. With logarithm transformation, the correlat...

This paper presents an efficient Harmonic-CELP hybrid coder at 2.4 kbps utilizing the well-known characteristics of the Harmonic and CELP coders. According to frame voicing decision, the proposed hybrid coder switches the RP-VSELP coder as a fast CELP in case of unvoiced, or an improved Harmonic coder in case of voiced. The proposed Harmonic-CELP hybrid coder has several features as follows: fa...