25,257 research outputs found

    Parametric Compositional Data Types

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    In previous work we have illustrated the benefits that compositional data types (CDTs) offer for implementing languages and in general for dealing with abstract syntax trees (ASTs). Based on Swierstra's data types \'a la carte, CDTs are implemented as a Haskell library that enables the definition of recursive data types and functions on them in a modular and extendable fashion. Although CDTs provide a powerful tool for analysing and manipulating ASTs, they lack a convenient representation of variable binders. In this paper we remedy this deficiency by combining the framework of CDTs with Chlipala's parametric higher-order abstract syntax (PHOAS). We show how a generalisation from functors to difunctors enables us to capture PHOAS while still maintaining the features of the original implementation of CDTs, in particular its modularity. Unlike previous approaches, we avoid so-called exotic terms without resorting to abstract types: this is crucial when we want to perform transformations on CDTs that inspect the recursively computed CDTs, e.g. constant folding.Comment: In Proceedings MSFP 2012, arXiv:1202.240

    Speech vocoding for laboratory phonology

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    Using phonological speech vocoding, we propose a platform for exploring relations between phonology and speech processing, and in broader terms, for exploring relations between the abstract and physical structures of a speech signal. Our goal is to make a step towards bridging phonology and speech processing and to contribute to the program of Laboratory Phonology. We show three application examples for laboratory phonology: compositional phonological speech modelling, a comparison of phonological systems and an experimental phonological parametric text-to-speech (TTS) system. The featural representations of the following three phonological systems are considered in this work: (i) Government Phonology (GP), (ii) the Sound Pattern of English (SPE), and (iii) the extended SPE (eSPE). Comparing GP- and eSPE-based vocoded speech, we conclude that the latter achieves slightly better results than the former. However, GP - the most compact phonological speech representation - performs comparably to the systems with a higher number of phonological features. The parametric TTS based on phonological speech representation, and trained from an unlabelled audiobook in an unsupervised manner, achieves intelligibility of 85% of the state-of-the-art parametric speech synthesis. We envision that the presented approach paves the way for researchers in both fields to form meaningful hypotheses that are explicitly testable using the concepts developed and exemplified in this paper. On the one hand, laboratory phonologists might test the applied concepts of their theoretical models, and on the other hand, the speech processing community may utilize the concepts developed for the theoretical phonological models for improvements of the current state-of-the-art applications

    A Unified Framework for Compositional Fitting of Active Appearance Models

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    Active Appearance Models (AAMs) are one of the most popular and well-established techniques for modeling deformable objects in computer vision. In this paper, we study the problem of fitting AAMs using Compositional Gradient Descent (CGD) algorithms. We present a unified and complete view of these algorithms and classify them with respect to three main characteristics: i) cost function; ii) type of composition; and iii) optimization method. Furthermore, we extend the previous view by: a) proposing a novel Bayesian cost function that can be interpreted as a general probabilistic formulation of the well-known project-out loss; b) introducing two new types of composition, asymmetric and bidirectional, that combine the gradients of both image and appearance model to derive better conver- gent and more robust CGD algorithms; and c) providing new valuable insights into existent CGD algorithms by reinterpreting them as direct applications of the Schur complement and the Wiberg method. Finally, in order to encourage open research and facilitate future comparisons with our work, we make the implementa- tion of the algorithms studied in this paper publicly available as part of the Menpo Project.Comment: 39 page

    Summary-based inference of quantitative bounds of live heap objects

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    This article presents a symbolic static analysis for computing parametric upper bounds of the number of simultaneously live objects of sequential Java-like programs. Inferring the peak amount of irreclaimable objects is the cornerstone for analyzing potential heap-memory consumption of stand-alone applications or libraries. The analysis builds method-level summaries quantifying the peak number of live objects and the number of escaping objects. Summaries are built by resorting to summaries of their callees. The usability, scalability and precision of the technique is validated by successfully predicting the object heap usage of a medium-size, real-life application which is significantly larger than other previously reported case-studies.Fil: Braberman, Victor Adrian. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de ComputaciĂłn; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂŠcnicas; ArgentinaFil: Garbervetsky, Diego David. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de ComputaciĂłn; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂŠcnicas; ArgentinaFil: Hym, Samuel. Universite Lille 3; FranciaFil: Yovine, Sergio Fabian. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de ComputaciĂłn; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂŠcnicas; Argentin

    Compositional Performance Modelling with the TIPPtool

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    Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations

    A Permutation-based Combination of Sign Tests for Assessing Habitat Selection

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    The analysis of habitat use in radio-tagged animals is approached by comparing the portions of use vs the portions of availability observed for each habitat type. Since data are linearly dependent with singular variance-covariance matrices, standard multivariate statistical test cannot be applied. To overcome the problem, compositional data analysis is customary performed via log-ratio transform of sample observations. The procedure is criticized in this paper, emphasizing the many drawbacks which may arise from the use of compositional analysis. An alternative nonparametric solution is proposed in the framework of multiple testing. The habitat use is assessed separately for each habitat type by means of the sign test performed on the original observations. The resulting p-values are combined in an overall test statistic whose significance is determined permuting sample observations. The theoretical findings of the paper are checked by simulation studies. Applications to some case studies are considered.compositional data analysis, Johnson’s second order selection, Johnson’s third order selection, Monte Carlo studies, multiple testing, random habitat use.

    Too good to be true: pitfalls of usingmean Ellenberg indicator values in vegetation analyses

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    Question: Mean Ellenberg indicator values (EIVs) inherit information about compositional similarity, because during their calculation species abundances (or presence–absences) are used as weights. Can this similarity issue actually be demonstrated, does it bias results of vegetation analyses correlating mean EIVs with other aspects of species composition and how often are biased studies published? Methods: In order to separate information on compositional similarity possibly present in mean EIVs, a new variable was introduced, calculated as a weighted average of randomized species EIVs. The performance of these mean randomized EIVs was compared with that of the mean real EIVs on the one hand and random values (randomized mean EIVs) on the other. To demonstrate the similarity issue, differences between samples were correlated with dissimilarity matrices based on various indices. Next, the three mean EIV variables were tested in canonical correspondence analysis (CCA), detrended correspondence analysis (DCA), analysis of variance (ANOVA) between vegetation clusters, and in regression on species richness. Subsequently, a modified permutation test of significance was proposed, taking the similarity issue into account. In addition, an inventory was made of studies published in the Journal of Vegetation Science and Applied Vegetation Science between 2000 and 2010 likely reporting biased results due to the similarity issue. Results: Using mean randomized EIVs, it is shown that compositional similarity is inherited into mean EIVs and most resembles the inter-sample distances in correspondence analysis, which itself is based on iterative weighted averaging. The use of mean EIVs produced biased results in all four analysis types examined: unrealistic (too high) explained variances in CCA, too many significant correlations with ordination axes in DCA, too many significant differences between cluster analysis groups and too high coefficients of determination in regressions on species richness. Modified permutation tests provided ecologically better interpretable results. From 95 studies using Ellenberg indicator values, 36 reported potentially biased results. Conclusions: No statistical inferences should bemade in analyses relatingmean EIVs with other variables derived from the species composition as this can produce highly biased results, leading to misinterpretation. Alternatively, a modified permutation test using mean randomized EIVs can sometimes be used

    Regression analysis with compositional data containing zero values

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    Regression analysis with compositional data containing zero valuesComment: The paper has been accepted for publication in the Chilean Journal of Statistics. It consists of 12 pages with 4 figure
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