Recently recognition of emotions became very important in the field of speech and/or speaker recognition. This paper is dedicated to experimental investigation of best acoustic features obtained for purpose of gender-dependent speaker recognition from emotional speech. Four feature sets LPC (Linear Prediction Coefficients), LPCC (Linear Prediction Cepstral Coefficients), MFCC (Melfrequency Ceps...

This paper presents a new technique to index and retrieve texture image. The image is modeled with the two-dimensional one-sided linear prediction (OSP) model. The prediction coefficients, normalized mean-square prediction error and a set of seven invariant moments of the prediction error are used as features to index the image. The proposed method is highly successful in retrieving perceptuall...

A new impulse noise detection technique from gray-scale and multichannel images is presented. It is based on block correlation of the noncausal linear prediction. The linear prediction coefficients are calculated using a block of the image at one instant. These coefficients are valid within that block only and are used to predict a pixel in a sliding window within the block. The sample is predi...

Multivariable regression and artificial neural network procedures were used to modeling of the input power and gas holdup of flotation. The stepwise nonlinear equations have shown greater accuracy than linear ones where they can predict input power, and gas holdup with the correlation coefficients of 0.79 thereby 0.51 in the linear, and R2=0.88 versus 0.52 in the non linear, respectively. ...

Several alternate linear prediction parametric representations are experimentally compared as to their vowel recognition performance. The speech data used for this purpose consist of 900 utterances of 10 different vowels spoken by 3 speakers in a/b/-vowel-/b/context. The cepstral coefficients representation is found to be the best linear prediction parametric representation. ~chantillons de 10 ...

− In this paper a simple algorithm to detect an emergency vehicle’s siren using the linear prediction is presented. By measuring the means and variances of the reflection coefficients in a preselected number of successive frames, automatic detection of emergency vehicle’s siren is possible. It has been shown that only two coefficients are enough for successful detection. Due to the simplicity o...

In this paper, a new method is presented to extract robust speech features in the presence of the external noise. The proposed method based on two-dimensional Gabor filters takes in account the spectro-temporal modulation frequencies and also limits the redundancy on the feature level. The performance of the proposed feature extraction method was evaluated on isolated speech words which are ext...

In this contribution, a time-varying linear prediction method is applied to speech processing. In contrast to the commonly used linear prediction approach, the proposed time-varying method considers the continuous time evolution of the vocal tract and, additionally, avoids block-wise processing. On the assumption that the linear predictor coefficients evolve linearly in sections and continuousl...

We propose a novel method for lossless compression of ultraspectral sounder data. The spectral utilizes linear prediction and the optimal ordering of the granules. The prediction coefficients for a granule are computed using prediction coefficients that are optimized using a different granule. The optimal ordering problem is solved using Edmonds 's algorithm branching. optimum show results that...

The automatic speaker verification spoofing and countermeasures challenge 2015 provides a common framework for the evaluation of spoofing countermeasures or anti-spoofing techniques in the presence of various seen and unseen spoofing attacks. This contribution proposes a system consisting of amplitude, phase, linear prediction residual, and combined amplitude phase-based countermeasures for the...