This paper proposes a fast method of calculating high-order backward Linear Prediction (LP) coefficients for wideband Code Excited LP (CELP) coders operating at around 16 kbit/s. The fast calculation is achieved by a recursive calculation for the high-order autocorrelation of the decoded signal. The recursive calculation can be employed thanks to a novel method of converting the autocorrelation...

In this paper, we propose several compensation approaches to alleviate the effect of additive noise on speech features for speech recognition. These approaches are simple yet efficient noise reduction techniques that use online constructed pseudo stereo codebooks to evaluate the statistics in both clean and noisy environments. The process yields transforms for noise-corrupted speech features to...

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequencyselective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by ...

We present a method to predict the time thatwill be needed to traverse a certain stretch of freeway whendeparture is at a certain time in the future. The predic-tion is done on the basis of the current traffic situation incombination with historical data.We argue that, for our purpose, the current situation of astretch of freeway is well summarized by the ‘current status...

The present work demonstrates experimental evaluation of speaker verification for different speech feature extraction techniques with the constraints of limited data (less than 15 seconds). The state-of-the-art speaker verification techniques provide good performance for sufficient data (greater than 1 minutes). It is a challenging task to develop techniques which perform well for speaker verif...

the objective of the present study was to estimate genetic trends for lactation milk yield, persistency of milk yield, somatic cell count and interval between first and second calving in holstein dairy cows of iran. the dataset consisted of 210,625 test day and 25,883 first parity cows with milk yield recorded from july 2002 to september 2007 comprising 97 herds in iran. breeding values of anim...

Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in which regression coefficients are themselves given a model, whose parameters are also estimated from data. We illustrate the strengths and limitations of multilevel modeling through an example of the prediction of home radon levels in U.S. counties. The multilevel model is highly effective for pr...

Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in which regression coefficients are themselves given a model, whose parameters are also estimated from data. We illustrate the strengths and limitations of multilevel modeling through an example of the prediction of home radon levels in U.S. counties. The multilevel model is highly effective for pr...

An on-line signature verification scheme based on linear prediction coding (LPC) cepstrum and neural networks is proposed. Cepstral coefficients derived from linear predictor coefficients of the writing trajectories are calculated as the features of the signatures. These coefficients are used as inputs to the neural networks. A number of single-output multilayer perceptrons (MLPs), as many as t...

In this extended abstract we introduce a new method for eliciting experts, prior knowledge about the similarity of the roles of features in the prediction task. The key idea is to use an interactive multidimensional-scaling-type scatterplot display of the features to elicit the similarity relationships, and then use the elicited relationships in the prior distribution of prediction parameters. ...