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Editor for this issue: Helen Dry <hdryemunix.emich.edu>
central.cis.upenn.edu>The following new technical reports are now available from the Institute for Research in Cognitive Science: Probabilistic Matching of Brain Images J.C. Gee L. LeBriquer C. Barillot D.R. Haynor IRCS-95-07 $2.20 Image matching has emerged as an important area of investigation in medical image analysis. In particular, much attention has been focused on the atlas problem, in which a template representing the structural anatomy of the human brain is deformed to match anatomic brain images from a given individual. The problem is made difficult because there are important differences in both the gross and local morphology of the brain among normal individuals. We have formulated the image matching problem under a Bayesian framework. The Bayesian methodology facilitates a principled approach to the development of a matching model. Of special interest is its capacity to deal with uncertainty in the estimates, a potentially important but generally ignored aspect of the solution. In the construction of a reference system for the human brain, the Bayesian approach is well suited to the task of modeling variation in morphology. Statistical information about morphological variability, accumulated over past samples, can be formally introduced into the problem formulation to guide the matching or normalization of future data sets. Bayesian Approach to the Brain Image Matching Problem J.C. Gee L. LeBriquer C. Barillot D.R. Haynor R. Bajcsy IRCS-95-08 $1.80 The application of image matching to the problem of localizing structural anatomy in images of the human brain forms the specific aim of our work. The interpretation of such images is a difficult task for human observers because of the many ways in which the identity of a given structure can be obscured. Our approach is based on the assumption that a common topology underlies the anatomy of normal individuals. To the degree that this assumption holds, the localization problem can be solved by determining the mapping from the anatomy of a given individual to some referential atlas of cerebral anatomy. Previous such approaches have in many cases relied on a physical interpretation of this mapping. In this paper, we examine a more general Bayesian formulation of the image matching problem and demonstrate the approach on two-dimensional magnetic resonance images. XTAG System - A Wide Coverage Grammar for English Christy Doran Dania Egedi Beth Ann Hockey B. Srinivas Martin Zaidel IRCS-95-09 $1.03 This paper presents the XTAG system, a grammar development tool based on the Tree Adjoining Grammar (TAG) formalism that includes a wide-coverage syntactic grammar for English. The various components of the system are discussed and preliminary evaluation results from the parsing of various corpora are given. Results from the comparison of XTAG against the IBM statistical parser and the Alvey Natural Language Tool parser are also given. Disambiguation of Super Parts of Speech (or Supertags): Almost Parsing Aravind K. Joshi B. Srinivas IRCS-95-10 $1.28 In a lexicalized grammar formalism such as Lexicalized Tree-Adjoining Grammar (LTAG), each lexical item is associated with at least one elementary structure (supertag) that localizes syntactic and semantic dependencies. Thus a parser for a lexicalized grammar must search a large set of supertags to choose the right ones to combine for the parse of the sentence. We present techniques for disambiguating supertags using local information such as lexical preference and local lexical dependencies. The similarity between LTAG and Dependency grammars is exploited in the dependency model of supertag disambiguation. The performance results for various models of supertag disambiguation such as unigram, trigram and dependency-based models are presented. A Freely Available Syntactic Lexicon for English Dania Egedi Patrick Martin IRCS-95-11 $1.18 This paper presents a syntactic lexicon for English that was originally derived from the Oxford Advanced Learner's Dictionary and the Oxford Dictionary of Current Idiomatic English, and then modified and augmented by hand. There are more than 37,000 syntactic entries from all 8 parts of speech. An X-windows based tool is available for maintaining the lexicon and performing searches. C and Lisp hooks are also available so that the lexicon can be easily utilized by parsers and other programs. Lexicalization and Grammar Development B. Srinivas Dania Egedi Christy Doran Tilman Becker IRCS-95-12 $1.18 In this paper we present a fully lexicalized grammar formalism as a particularly attractive framework for the specification of natural language grammars. We discuss in detail Feature-based, Lexicalized Tree Adjoining Grammars (FB-LTAGs), a representative of the class of lexicalized grammars. We illustrate the advantages of lexicalized grammars in various contexts of natural language processing, ranging from wide-coverage grammar development to parsing and machine translation. We also present a method for compact and efficient representation of lexicalized trees. A Processing Model for Free Word Order Languages Owen Rambow Aravind K. Joshi IRCS-95-13 $2.00 Like many verb-final languages, German displays considerable word-order freedom: there is no syntactic constraint on the ordering of the nominal arguments of a verb, as long as the verb remains in final position. This effect is referred to as ``scrambling'', and is interpreted in transformational frameworks as leftward movement of the arguments. Furthermore, arguments from an embedded clause may move out of their clause; this effect is referred to as ``long-distance scrambling''. While scrambling has recently received considerable attention in the syntactic literature, the status of long-distance scrambling has only rarely been addressed. The reason for this is the problematic status of the data: not only is long-distance scrambling highly dependent on pragmatic context, it also is strongly subject to degradation due to processing constraints. As in the case of center-embedding, it is not immediately clear whether to assume that observed unacceptability of highly complex sentences is due to grammatical restrictions, or whether we should assume that the competence grammar does not place any restrictions on scrambling (and that, therefore, all such sentences are in fact grammatical), and the unacceptability of some (or most) of the grammatically possible word orders is due to processing limitations. In this paper, we will argue for the second view by presenting a processing model for German. **************************************************************************** How to access reports: The reports are available in bound form for the price listed above, or may be obtained for free, electronically. To obtain a compressed postscript copy of the report, open an anonymous ftp session on ftp.cis.upenn.edu path: pub/ircs/technical-reports The files are named according to their number. For example, Report 95-01 is stored as 95-01.ps.Z, 95-02 is stored as 95-02.ps.Z, etc. If you are using ftp, change the setting to binary and download the file. To get a copy of Report 95-01, you would type: binary get 95-01.ps.Z You can also obtain files through electronic mail. Send a mail message to ircsservMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issue