170 resultados para Analogy (Linguistics)


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Statistical methods of describing prosody were used to study fluency, expressiveness and their relationship among 8-10-year-old readers. There were robust relationships between expressiveness and variables associated with pitch mobility; and between fluency and measures associated with temporal organization. Interactions indicated that the relationships were not simple. Differences between groups depended on sentence content and position. Some measures offer a basis for rules aimed at assigning individuals to skill categories. The effects suggest psychological hypotheses about the underlying mechanisms.

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This paper examines the importance of British contributions to the success of the Irish hospitals sweepstake. In its early years, up to three-quarters of these tickets were sold in Britain, bringing millions of pounds into Ireland annually to improve and expand the state's hospitals. The vast amount of money leaving Britain in this way angered the British government and forced it to introduce new legislation to curtail the activities of the Irish sweep. The paper will highlight the extent to which the success of the sweepstake depended on the market for tickets in Britain; the threat to the sweep's survival posed by the restriction of its activities in Britain after 1935; the role of the sweepstake controversy in exacerbating further already strained relations between Britain and the Irish Free State in the 1930s; how the success of the sweep raised the issue of legalising a British lottery; and the eventual decline of the sweepstake as a force in British gambling in the post-war years.

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This paper provides a summary of our studies on robust speech recognition based on a new statistical approach – the probabilistic union model. We consider speech recognition given that part of the acoustic features may be corrupted by noise. The union model is a method for basing the recognition on the clean part of the features, thereby reducing the effect of the noise on recognition. To this end, the union model is similar to the missing feature method. However, the two methods achieve this end through different routes. The missing feature method usually requires the identity of the noisy data for noise removal, while the union model combines the local features based on the union of random events, to reduce the dependence of the model on information about the noise. We previously investigated the applications of the union model to speech recognition involving unknown partial corruption in frequency band, in time duration, and in feature streams. Additionally, a combination of the union model with conventional noise-reduction techniques was studied, as a means of dealing with a mixture of known or trainable noise and unknown unexpected noise. In this paper, a unified review, in the context of dealing with unknown partial feature corruption, is provided into each of these applications, giving the appropriate theory and implementation algorithms, along with an experimental evaluation.

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We exploit the analogy between the transfer of a pulse across a scattering medium and Aharonov's weak measurements to resolve the long standing paradox between the impossibility to exceed the speed of light and the seemingly "superluminal" behavior of a tunneling particle in the barrier or a photon in a "fast-light" medium. We demonstrate that superluminality occurs when the value of the duration tau spent in the barrier is uncertain, whereas when tau is known accurately, no superluminal behavior is observed. In all cases only subluminal durations contribute to the transmission which precludes faster-than-light information transfer, as observed in a recent experiment.

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The article explores the themes of fluidity and immobility in the works of Ying Chen, a francophone Chinese writer whose early texts are associated with 'les écritures migrantes' of Quebec. From her third book, the narratives take on a post-death perspective and the narrator moves between her present existence and past lives.

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We describe an empirical, self-consistent, orthogonal tight-binding model for zirconia, which allows for the polarizability of the anions at dipole and quadrupole levels and for crystal field splitting of the cation d orbitals, This is achieved by mixing the orbitals of different symmetry on a site with coupling coefficients driven by the Coulomb potentials up to octapole level. The additional forces on atoms due to the self-consistency and polarizabilities are exactly obtained by straightforward electrostatics, by analogy with the Hellmann-Feynman theorem as applied in first-principles calculations. The model correctly orders the zero temperature energies of all zirconia polymorphs. The Zr-O matrix elements of the Hamiltonian, which measure covalency, make a greater contribution than the polarizability to the energy differences between phases. Results for elastic constants of the cubic and tetragonal phases and phonon frequencies of the cubic phase are also presented and compared with some experimental data and first-principles calculations. We suggest that the model will be useful for studying finite temperature effects by means of molecular dynamics.

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The Zipf curves of log of frequency against log of rank for a large English corpus of 500 million word tokens, 689,000 word types and for a large Spanish corpus of 16 million word tokens, 139,000 word types are shown to have the usual slope close to –1 for rank less than 5,000, but then for a higher rank they turn to give a slope close to –2. This is apparently mainly due to foreign words and place names. Other Zipf curves for highlyinflected Indo-European languages, Irish and ancient Latin, are also given. Because of the larger number of word types per lemma, they remain flatter than the English curve maintaining a slope of –1 until turning points of about ranks 30,000 for Irish and 10,000 for Latin. A formula which calculates the number of tokens given the number of types is derived in terms of the rank at the turning point, 5,000 for both English and Spanish, 30,000 for Irish and 10,000 for Latin.