Error statistics

Xem 1-20 trên 95 kết quả Error statistics
  • Probability and statistics are concerned with events which occur by chance. Examples include occurrence of accidents, errors of measurements, production of defective and nondefective items from a production line, and various games of chance, such as drawing a card from a well-mixed deck, flipping a coin, or throwing a symmetrical six-sided die. In each case we may have some knowledge of the likelihood of various possible results, but we cannot predict with any certainty the outcome of any particular trial....

    pdf417p sofia11 25-05-2012 90 38   Download

  • If you need to create and interpret statistics in business or classroom settings, this easy-to-use guide is just what you need. It shows you how to use Excel's powerful tools for statistical analysis, even if you've never taken a course in statistics. Learn the meaning of terms like mean and median, margin of error, standard deviation, and permutations, and discover how to interpret the statistics of everyday life. You'll learn to use Excel formulas, charts, PivotTables, and other tools to make sense of everything from sports stats to medical correlations....

    pdf530p ringphone 06-05-2013 74 37   Download

  • Sampling and descriptive statistics, probability, propagation of error, commonly used distributions, confidence intervals, hypothesis testing, correlation and simple linear regression, multiple regression,... As the main contents of the ebook "Statistics for Engineers and Scientists". Invite you to consult.

    pdf933p bigg421996 03-12-2015 38 18   Download

  • Most statistical machine translation systems employ a word-based alignment model. In this paper we demonstrate that word-based alignment is a major cause of translation errors. We propose a new alignment model based on shallow phrase structures, and the structures can be automatically acquired from parallel corpus. This new model achieved over 10% error reduction for our spoken language translation task.

    pdf7p bunrieu_1 18-04-2013 19 4   Download

  •   Nowadays,  digital  terrain  models  (DTM)  are  an  important  source  of  spatial  data  for  various  applications  in  many  scientific  disciplines.  Therefore,  special  attention  is  given  to  their  main characteristic ‐ accuracy. At it is well known, the source data for DTM creation contributes a  large amount  of errors, including gross errors, to the final product.

    pdf7p dem_thanh 22-12-2012 21 3   Download

  • Medical Statistics at a Glance is directed at undergraduate medical students, medical researchers, postgraduates in the biomedical disciplines and at pharmaceutical industry personnel. All of these individuals will, at some time in their professional lives, be faced with quantitative results (their own or those of others) that will need to be critically evaluated and interpreted, and some, of course, will have to pass that dreaded statistics exam! A proper understanding of statistical concepts and methodology is invaluable for these needs.

    pdf139p hyperion75 22-01-2013 38 3   Download

  • Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality. These training criteria make use of recently proposed automatic evaluation metrics.

    pdf8p bunbo_1 17-04-2013 18 3   Download

  • This paper focuses on the analysis and prediction of so-called aware sites, defined as turns where a user of a spoken dialogue system first becomes aware that the system has made a speech recognition error. We describe statistical comparisons of features of these aware sites in a train timetable spoken dialogue corpus, which reveal significant prosodic differences between such turns, compared with turns that ‘correct’ speech recognition errors as well as with ‘normal’ turns that are neither aware sites nor corrections. ...

    pdf8p bunrieu_1 18-04-2013 18 3   Download

  • It is important to correct the errors in the results of speech recognition to increase the performance of a speech translation system. This paper proposes a method for correcting errors using the statistical features of character co-occurrence, and evaluates the method. The proposed method comprises two successive correcting processes. The first process uses pairs of strings: the first string is an erroneous substring of the utterance predicted by speech recognition, the second string is the corresponding section of the actual utterance.

    pdf5p bunrieu_1 18-04-2013 28 3   Download

  • We present a novel OCR error correction method for languages without word delimiters that have a large character set, such as Japanese and Chinese. It consists of a statistical OCR model, an approximate word matching method using character shape similarity, and a word segmentation algorithm using a statistical language model. By using a statistical OCR model and character shape similarity, the proposed error corrector outperforms the previously published method. When the baseline character recognition accuracy is 90%, it achieves 97.4% character recognition accuracy. ...

    pdf7p bunrieu_1 18-04-2013 21 3   Download

  • Statistical methods require very large corpus with high quality. But building large and faultless annotated corpus is a very difficult job. This paper proposes an efficient m e t h o d to construct part-of-speech tagged corpus. A rulebased error correction m e t h o d is proposed to find and correct errors semi-automatically by user-defined rules. We also make use of user's correction log to reflect feedback. Experiments were carried out to show the efficiency of error correction process of this workbench. The result shows that about 63.2 % of tagging errors can be corrected. ...

    pdf5p bunrieu_1 18-04-2013 18 3   Download

  • (BQ) Part 1 book "A handbook of applied statistics in pharmacology" presents the following contents: Probability, distribution; mean, mode, median; variance, standard deviation, standard error, coefficient of variation; analysis of normality and homogeneity of variance; transformation of data and outliers; tests for significant differences,...

    pdf120p thangnamvoiva6 19-07-2016 18 3   Download

  • In this thesis proposal I present my thesis work, about pre- and postprocessing for statistical machine translation, mainly into Germanic languages. I focus my work on four areas: compounding, definite noun phrases, reordering, and error correction. Initial results are positive within all four areas, and there are promising possibilities for extending these approaches.

    pdf6p hongdo_1 12-04-2013 21 2   Download

  • Minimum Error Rate Training (MERT) and Minimum Bayes-Risk (MBR) decoding are used in most current state-of-theart Statistical Machine Translation (SMT) systems. The algorithms were originally developed to work with N -best lists of translations, and recently extended to lattices that encode many more hypotheses than typical N -best lists. We here extend lattice-based MERT and MBR algorithms to work with hypergraphs that encode a vast number of translations produced by MT systems based on Synchronous Context Free Grammars.

    pdf9p hongphan_1 14-04-2013 25 2   Download

  • The development of Dialog-Based ComputerAssisted Language Learning (DB-CALL) systems requires research on the simulation of language learners. This paper presents a new method for generation of grammar errors, an important part of the language learner simulator. Realistic errors are generated via Markov Logic, which provides an effective way to merge a statistical approach with expert knowledge about the grammar error characteristics of language learners. Results suggest that the distribution of simulated grammar errors generated by the proposed model is similar to that of real learners.

    pdf4p hongphan_1 15-04-2013 26 2   Download

  • We describe a statistical technique for assigning senses to words. An instance of a word is assigned a sense by asking a question about the context in which the word appears. The question is constructed to have high mutual information with the translation of that instance in another language. When we incorporated this method of assigning senses into our statistical machine translation system, the error rate of the system decreased by thirteen percent. language model does not realize that take my own decision is improbable because take and decision no longer fall within a single trigram. ...

    pdf7p bunmoc_1 20-04-2013 23 2   Download

  • We evaluate measures of contextual fitness on the task of detecting real-word spelling errors. For that purpose, we extract naturally occurring errors and their contexts from the Wikipedia revision history. We show that such natural errors are better suited for evaluation than the previously used artificially created errors. In particular, the precision of statistical methods has been largely over-estimated, while the precision of knowledge-based approaches has been under-estimated.

    pdf10p bunthai_1 06-05-2013 27 2   Download

  • In this chapter you will learn: Define a point estimator, a point estimate, and desirable properties of a point estimator such as unbiasedness, efficiency, and consistency; define an interval estimator and an interval estimate; define a confidence interval, confidence level, margin of error, and a confidence interval estimate;...

    ppt45p tangtuy09 21-04-2016 21 2   Download

  • When you have completed this chapter, you will be able to: Define null and alternative hypothesis and hypothesis testing, define Type I and Type II errors, describe the five-step hypothesis testing procedure, distinguish between a one-tailed and a two-tailed test of hypothesis,...

    ppt53p tangtuy09 21-04-2016 20 2   Download

  • tation schemes in different projects are usually different, since the underlying linguistic theories vary and have different ways to explain the same language phenomena. Though statistical NLP systems usually are not bound to specific annotation standards, almost all of them assume homogeneous annotation in the training corpus.

    pdf10p nghetay_1 07-04-2013 17 1   Download


Đồng bộ tài khoản