10 resultados para Arabic language--Figures of speech--Early works to 1800

em Indian Institute of Science - Bangalore - Índia


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This correspondence describes a method for automated segmentation of speech. The method proposed in this paper uses a specially designed filter-bank called Bach filter-bank which makes use of 'music' related perception criteria. The speech signal is treated as continuously time varying signal as against a short time stationary model. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. The Bach filters are seen to marginally outperform the other filters.

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This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.

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We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

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At 2-3 h after phenobaribtal administration, the drug has no effect on nucleoplasmic RNA synthesis and decreases nucleolar RNA synthesis. However, at this time there is an increase in the labelling of cytoplasmic poly(A)-containing RNA, even though there is decreased labelling of total polyribosomal RNA. The decrease in labelling of nucleolar and total polyribosomal RNA owing to phenobarbital is a transient phenomenon. Under similar conditions, 3-methylcholanthrene has no effect on nucleolar RNA synthesis, but leads to an increase in synthesis of nucleoplasmic and cytoplasmic poly(A)-containing RNA. Cytosol isolated from phenobarbital-treated, but not from 3-methyl-cholanthrene-treated, animals facilitates an enhanced transport of RNA from nuclei. At the time points investigated, 3-methylcholanthrene or its metabolite shows a 10-15-fold higher concentration in the chromatin than that of phenobarbital or its metabolite. It is suggested that the primary effect of phenobarbital is at the cytoplasmic level, promoting the transport of RNA from the nuclei, which can act as a trigger for enhanced transcription at later periods. 3-Methylcholanthrene or its metabolite directly binds to the chromatin and evokes a selective transcriptional response.

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It has been noted that at high energy the Ricci scalar is manifested in two different ways, as a matter field as well as a geometrical field (which is its usual nature even at low energy). Here, using the material aspect of the Ricci scalar, its interaction with Dirac spinors is considered in four-dimensional curved spacetime. We find that a large number of fermion-antifermion pairs can be produced by the exponential expansion of the early universe.

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Laminar separation bubbles are thought to be highly non-parallel, and hence global stability studies start from this premise. However, experimentalists have always realized that the flow is more parallel than is commonly believed, for pressure-gradient-induced bubbles, and this is why linear parallel stability theory has been successful in describing their early stages of transition. The present experimental/numerical study re-examines this important issue and finds that the base flow in such a separation bubble becomes nearly parallel due to a strong-interaction process between the separated boundary layer and the outer potential flow. The so-called dead-air region or the region of constant pressure is a simple consequence of this strong interaction. We use triple-deck theory to qualitatively explain these features. Next, the implications of global analysis for the linear stability of separation bubbles are considered. In particular we show that in the initial portion of the bubble, where the flow is nearly parallel, local stability analysis is sufficient to capture the essential physics. It appears that the real utility of the global analysis is perhaps in the rear portion of the bubble, where the flow is highly non-parallel, and where the secondary/nonlinear instability stages are likely to dominate the dynamics.

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This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.

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We consider the speech production mechanism and the asso- ciated linear source-filter model. For voiced speech sounds in particular, the source/glottal excitation is modeled as a stream of impulses and the filter as a cascade of second-order resonators. We show that the process of sampling speech signals can be modeled as filtering a stream of Dirac impulses (a model for the excitation) with a kernel function (the vocal tract response),and then sampling uniformly. We show that the problem of esti- mating the excitation is equivalent to the problem of recovering a stream of Dirac impulses from samples of a filtered version. We present associated algorithms based on the annihilating filter and also make a comparison with the classical linear prediction technique, which is well known in speech analysis. Results on synthesized as well as natural speech data are presented.

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A joint analysis-synthesis framework is developed for the compressive sensing (CS) recovery of speech signals. The signal is assumed to be sparse in the residual domain with the linear prediction filter used as the sparse transformation. Importantly this transform is not known apriori, since estimating the predictor filter requires the knowledge of the signal. Two prediction filters, one comb filter for pitch and another all pole formant filter are needed to induce maximum sparsity. An iterative method is proposed for the estimation of both the prediction filters and the signal itself. Formant prediction filter is used as the synthesis transform, while the pitch filter is used to model the periodicity in the residual excitation signal, in the analysis mode. Significant improvement in the LLR measure is seen over the previously reported formant filter estimation.

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Thermoelectric (TE) conversion of waste heat into useful electricity demands optimized thermal and electrical transport in the leg material over a wide temperature range. In order to gain a reasonably high figure of merit (ZT) as well as high thermal electric conversion efficiency, various conditions of the starting material were studied: industrially produced skutterudite powders of p-type DDy(Fe1-xCox)(4)Sb-12 (DD: didymium) and n-type (Mm, Sm)(y)Co4Sb12 (Mm: mischmetal) were used. After a rather fast reaction-melting technique, the bulk was crushed and sieved with various strainers in order to obtain particles below the respective mesh sizes, followed by ball-milling under three different conditions. The dependence of the TE properties (after hot pressing) on the micro/nanosized particles, grains and crystallites was investigated. Optimized conditions resulted in an increase of ZT for bulk material to current record-high values: from ZT similar to 1.1 to ZT similar to 1.3 at 775 K for p-type and from ZT similar to 1.0 to ZT similar to 1.6 at 800 K for n-type, resulting in respective efficiencies (300-850 K) of eta > 13% and eta similar to 16%. (C) 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.