Time-domain eoders use long-term predietors to exploit the quasiperiodie strueture of voiced speech. However, one major drawbaek with classical predictors is the restriction of the delay to integer values, reducing the performance especially when the pitch period is short. This paper presents an extension of the prediction technique to encompass non-integer delays enabling more aeeurate represe...

We calculate the leading order interactions of massless D-brane excitations. Their 4-point functions are found to be identical to those found in type I theory. The amplitude for two massless D-brane fluctuations to produce a massless closed string is found to possess interesting new structure. As a function of its single kinematic invariant, it displays an infinite sequence of alternating zeros...

We propose an efficient solution to the problem of sparse linear prediction analysis of the speech signal. Our method is based on minimization of a weighted l2-norm of the prediction error. The weighting function is constructed such that less emphasis is given to the error around the points where we expect the largest prediction errors to occur (the glottal closure instants) and hence the resul...

This paper describes the application of deep neural networks (DNN), trained to discriminate between human and spoofed speech signals, to improve the performance of spoofing detection. In this work we use amplitude, phase, linear prediction residual, and combined amplitude phase-based acoustic level features. First we train a DNN on the spoofing challenge training data to discriminate between hu...

OBJECTIVE Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. METHODS The data set inclu...

In this chapter, we present the definition and principles of ultra-low bit-rate coders. Here the emphasis is to point to the fact that this class of coders is typically the ‘vocoders’, which are ‘parametric’ coders that are essentially linear-prediction (LP) based vocoders. This is in contrast to the ‘waveform’ coders, which operate at the higher bit-rates. Among the various frameworks employed...

This paper presents the Modi ed Multiband Excitation Model used for speech coding. In many MBE model coders, speech quality is degraded when incorrect voicing decisions are made, particularly for high-pitched female speakers. The MMBE addresses this issue with a modi ed voiced/unvoiced decision algorithm and a more robust pitch estimate. The listening quality of speech produced using the MMBE m...

In this paper we investigate the use of the feed-forward back propagation neural networks (FFBPNN) for automatic speech recognition of Arabic letters with their four vowels (Fatha, dhamma, Kasra, Soukoun). This investigation will constitute a basically step for the recognition of continuous Speech. Features were extracted from recorded corpus by using a variety of conventional methods such as L...

Regularized regression methods for linear regression have been developed the last few decades to overcome the flaws of ordinary least squares regression with regard to prediction accuracy. In this chapter, three of these methods (Ridge regression, the Lasso, and the Elastic Net) are incorporated into CATREG, an optimal scaling method for both linear and nonlinear transformation of variables in ...