2,573 research outputs found
Topic-based mixture language modelling
This paper describes an approach for constructing a mixture of language models based on simple statistical notions of semantics using probabilistic models developed for information retrieval. The approach encapsulates corpus-derived semantic information and is able to model varying styles of text. Using such information, the corpus texts are clustered in an unsupervised manner and a mixture of topic-specific language models is automatically created. The principal contribution of this work is to characterise the document space resulting from information retrieval techniques and to demonstrate the approach for mixture language modelling.
A comparison is made between manual and automatic clustering in order to elucidate how the global content information is expressed in the space. We also compare (in terms of association with manual clustering and language modelling accuracy) alternative term-weighting schemes and the effect of singular value decomposition dimension reduction (latent semantic analysis). Test set perplexity results using the British National Corpus indicate that the approach can improve the potential of statistical language modelling. Using an adaptive procedure, the conventional model may be tuned to track text data with a slight increase in computational cost
Efficient training algorithms for HMMs using incremental estimation
Typically, parameter estimation for a hidden Markov model (HMM) is performed using an expectation-maximization (EM) algorithm with the maximum-likelihood (ML) criterion. The EM algorithm is an iterative scheme that is well-defined and numerically stable, but convergence may require a large number of iterations. For speech recognition systems utilizing large amounts of training material, this results in long training times. This paper presents an incremental estimation approach to speed-up the training of HMMs without any loss of recognition performance. The algorithm selects a subset of data from the training set, updates the model parameters based on the subset, and then iterates the process until convergence of the parameters. The advantage of this approach is a substantial increase in the number of iterations of the EM algorithm per training token, which leads to faster training. In order to achieve reliable estimation from a small fraction of the complete data set at each iteration, two training criteria are studied; ML and maximum a posteriori (MAP) estimation. Experimental results show that the training of the incremental algorithms is substantially faster than the conventional (batch) method and suffers no loss of recognition performance. Furthermore, the incremental MAP based training algorithm improves performance over the batch versio
Emergent Phases of Nodeless and Nodal Superconductivity Separated by Antiferromagnetic Order in Iron-based Superconductor (Ca4Al2O6)Fe2(As1-xPx)2: 75As- and 31P-NMR Studies
We report P- and As-NMR studies on
(CaAlO)Fe(AsP) with an isovalent substitution
of P for As. We present the novel evolution of emergent phases that the
nodeless superconductivity (SC) in 00.4 and the nodal one around
=1 are intimately separated by the onset of a commensurate stripe-type
antiferromagnetic (AFM) order in 0.5 0.95, as an isovalent
substitution of P for As decreases a pnictogen height measured from
the Fe plane. It is demonstrated that the AFM order takes place under a
condition of 1.32\AA1.42\AA, which is also the case for other
Fe-pnictides with the Fe state in (Fe) layers. This novel
phase evolution with the variation in points to the importance of
electron correlation for the emergence of SC as well as AFM order.Comment: 5pages, 4figures; accepted for publication as a Rapid Communication
in Phys. Rev.
Glasgow University at TRECVID 2006
In the first part of this paper we describe our experiments in the automatic and interactive search tasks of TRECVID 2006. We submitted five fully automatic runs, including a text baseline, two runs based on visual features, and two runs that combine textual and visual features in a graph model. For the interactive search, we have implemented a new video search interface with relevance feedback facilities, based on both textual and visual features.
The second part is concerned with our approach to the high-level feature extraction task, based on textual information extracted from speech recogniser and machine translation outputs. They were aligned with shots and associated with high-level feature references. A list of significant words was created for each feature, and it was in turn utilised for identification of a feature during the evaluation
3D visual speech animation using 2D videos
In visual speech animation, lip motion accuracy is of paramount importance for speech intelligibility, especially for the hard of hearing or foreign language learners. We present an approach for visual speech animation that uses tracked lip motion in front-view 2D videos of a real speaker to drive the lip motion of a synthetic 3D head. This makes use of a 3D morphable model (3DMM), built using 3D synthetic head poses, with corresponding landmarks identified in the 2D videos and the 3DMM. We show that using a wider range of synthetic head poses for different phoneme intensities to create a 3DMM, as well as a combination of front and side photographs of the real speakers rather than just front photographs to produce initial neutral 3D synthetic head poses, gives better animation results when compared to ground truth data consisting of front-view 2D videos of real speakers
Conductivity and structure of a polyamide/silver iodide nanocomposite
This is a preprint of an article published in JOURNAL OF APPLIED POLYMER SCIENCE 2008; 108(5): 2814-2824ArticleJOURNAL OF APPLIED POLYMER SCIENCE. 108(5): 2814-2824 (2008)journal articl
Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs
We develop data structures for dynamic closest pair problems with arbitrary
distance functions, that do not necessarily come from any geometric structure
on the objects. Based on a technique previously used by the author for
Euclidean closest pairs, we show how to insert and delete objects from an
n-object set, maintaining the closest pair, in O(n log^2 n) time per update and
O(n) space. With quadratic space, we can instead use a quadtree-like structure
to achieve an optimal time bound, O(n) per update. We apply these data
structures to hierarchical clustering, greedy matching, and TSP heuristics, and
discuss other potential applications in machine learning, Groebner bases, and
local improvement algorithms for partition and placement problems. Experiments
show our new methods to be faster in practice than previously used heuristics.Comment: 20 pages, 9 figures. A preliminary version of this paper appeared at
the 9th ACM-SIAM Symp. on Discrete Algorithms, San Francisco, 1998, pp.
619-628. For source code and experimental results, see
http://www.ics.uci.edu/~eppstein/projects/pairs
Multifractal analysis for the ULF geomagnetic data during the 1993 Guam earthquake
International audienceIn our previous papers we have shown that the fractal (monofractal) dimension (Do) showed a significant increase before the Guam earthquake occurred on 8 August, 1993. In order to have a further support to this precursory effect to the general rupture (earthquake) we have carried out the corresponding multifractal analysis (by means of detrended fluctuation analysis) for the same data to study the statistical self-similar properties in a wide range of scales. We have analyzed the ULF geomagnetic data (the most intense H component) observed at Guam observatory. As the result, we have found that we could observe significant changes in the multifractal parameters at Guam such that ?min showed a meaningful decrease about 25 days before the earthquake and correspondingly ?? increased because ?max exhibited no significant change at all. The most sensitive parameter seems to be non-uniformity factor ?. Correspondingly, the generalized multifractal dimension Dq (q>1) showed a significant decrease (whereas Dq (qD0 (=Dq (q=0) (as already found in our previous papers) is reconfirmed to increase before the earthquake. These multifractal characteristics seem to be a further support that these changes are closely associated with the earthquake as a precursor to the Guam earthquake, providing us with appreciable information on the pre-rupture evolution of the earthquake
Electrospinning of poly (ether sulfone) and evaluation of the filtration efficiency
To produce high heat-resistant air filter, filtration properties of poly (ether sulfone) (PES) made by various electrospinning conditions were evaluated. The PES webs of 0.4-1.1 mu m average diameter fiber were obtained from 35-40 wt% PES / N,N- Dimethylacetamide (DMAc) solution. The diameter profile of electrospun PES web was clearly affected by PES concentration of the spinning dope and feeding rate of the dope, while the take-up speed effects little. The needle-collector distance affects the diameter profile for higher feeding rate conditions. The pore size of these webs was 1.3-5.6 mu m, which was decided not only average fiber diameter but also fiber diameter variation. Both filtration efficiency and pressure loss were dropped steeply at about 3.0 mu m of pore size. For the web having a pore size of 3.2 mu m, the pressure loss decrease to 215 Pa, while the filtration efficiency for 0.3 mu m particle kept 99.9998 %, which satisfied the HEPA requirement.ArticleSen'i Gakakishi. 63(12): 307-312 (2007)journal articl
Biosynthesis of O-phosphoserine-containing phosphoproteins by isolated bone cells of mouse calvaria
AbstractFive groups of isolated bone cells from mouse calvaria were incubated with [3H]serine and the presence and amount of O[3H]phosphoserine used as an indication of phosphoprotein synthesis. Cells in the osteoblastic fraction were the most active in synthesizing phosphoproteins, and unlike the other cell groups, released most of the phosphoproteins into the tissue culture medium. When subjected to molecular sieving and ion-exchange chromatography, the phosphoproteins synthesized by the bone cells of the osteoblastic group behaved like the phosphoproteins extracted from mouse calvaria by EDTA
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