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cS ( s, p) p th cepstral coefficient of the s th sub-bands { c1(1,p) = c(p) is the p th full-band cepstral parameter} S number of sub-bands Y(k) k th log spectral magnitude K number of log spectral magnitudes ′ k th log-energy outputs of the mel-scale filterbank Y ′ (k K ′ number of log-energy outputs of the mel-scale filterbank ht weight associated with the t th segment U number of competing speakers (1−ηs) average speaker verification error rate in the s th sub-band R, q number of sub-band-systems Superscript s implies the association of the s th sub-band Superscript u implies the association of the u th competing speaker Superscript r implies the association of the r th sub-band-system ′ implies the association of the complementary full-band cepstral parameters SB- Sub-band based DBSW dynamic band-limited segmental weights MFBO mel-scale filterbank output SNRW signal-to-noise ratio-based weighting factors CFBCC complementary full-band cepstral coefficient SSFCS sub-band system with full-band cepstral supplements MSBSA multiple sub-band-systems analysis FWN filtered white noise RNT real noise type

behaviors, or perhaps just as a preliminary filter for words suspicious enough to undergo a more accurate scrutiny. We consider in depth the simple probabilistic model in which sequences are produced by a random source emitting symbols from a known alphabet independently and according to a given

The usual expression for the secondary characteristical classes is regularized so that it fits for the case of Hilbert bundles. This gives index formulas for pseudodifferential operators with operator-valued symbols.

Feature weighting is known empirically to improve classification accuracy for k-nearest neighbor classifiers in tasks with irrelevant features. Many feature weighting algorithms are designed to work with symbolic features, or numeric features, or both, but cannot be applied to problems

decision procedure for the background the-ory. We provide novel algorithms for these operations and extend composition to symbolic transducers augmented with registers. Our base algorithms are unusual in that they are

Many mathematical algorithms are improved by the ability to provide the derivatives of functions. This paper presents a symbolic differentiator for Tcl: a Tcl function that operates on Tcl expressions and produces expressions that compute their derivatives. The differentiator exploits the little

-monial site remains of the Incan empire, and the silent symbolism of Stonehenge provide adequate evidence of man’s early interest in and acquaintance with cyclic patterns in nature. His culture has been developed around them and the interaction between those things im-posed by such natural rhythms and those

is unusual, and all the monks behave as though having such powers of memory is absolutely normal. Some investigation can prove that such an attitude toward education and memory is an accurate

, all subjects were given 15 minutes to write a supportive self-de-scriptive essay. Subjects who had been induced to be self-abasing were the least likely to interrupt themselves while writing the essay. The results of both studies are interpreted within the framework of symbolic self-completion theory