A Processing Model for Free Word Order Languages

Like many verb-final languages, Germn 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.Comment: 23 pages, uuencoded compressed ps file. In {\em Perspectives on Sentence Processing}, C. Clifton, Jr., L. Frazier and K. Rayner, editors. Lawrence Erlbaum Associates, 199

Temporal order processing of syllables in the left parietal lobe

Speech processing requires the temporal parsing of syllable order. Individuals suffering from posterior left hemisphere brain injury often exhibit temporal processing deficits as well as language deficits. Although the right posterior inferior parietal lobe has been implicated in temporal order judgments (TOJs) of visual information, there is limited evidence to support the role of the left inferior parietal lobe (IPL) in processing syllable order. The purpose of this study was to examine whether the left inferior parietal lobe is recruited during temporal order judgments of speech stimuli. Functional magnetic resonance imaging data were collected on 14 normal participants while they completed the following forced-choice tasks: (1) syllable order of multisyllabic pseudowords, (2) syllable identification of single syllables, and (3) gender identification of both multisyllabic and monosyllabic speech stimuli. Results revealed increased neural recruitment in the left inferior parietal lobe when participants made judgments about syllable order compared with both syllable identification and gender identification. These findings suggest that the left inferior parietal lobe plays an important role in processing syllable order and support the hypothesized role of this region as an interface between auditory speech and the articulatory code. Furthermore, a breakdown in this interface may explain some components of the speech deficits observed after posterior damage to the left hemisphere

First order algorithms in variational image processing

Variational methods in imaging are nowadays developing towards a quite universal and flexible tool, allowing for highly successful approaches on tasks like denoising, deblurring, inpainting, segmentation, super-resolution, disparity, and optical flow estimation. The overall structure of such approaches is of the form ${\cal D}(Ku) + \alpha {\cal R} (u) \rightarrow \min_u$ ; where the functional ${\cal D}$ is a data fidelity term also depending on some input data $f$ and measuring the deviation of $Ku$ from such and ${\cal R}$ is a regularization functional. Moreover $K$ is a (often linear) forward operator modeling the dependence of data on an underlying image, and $\alpha$ is a positive regularization parameter. While ${\cal D}$ is often smooth and (strictly) convex, the current practice almost exclusively uses nonsmooth regularization functionals. The majority of successful techniques is using nonsmooth and convex functionals like the total variation and generalizations thereof or $\ell_1$-norms of coefficients arising from scalar products with some frame system. The efficient solution of such variational problems in imaging demands for appropriate algorithms. Taking into account the specific structure as a sum of two very different terms to be minimized, splitting algorithms are a quite canonical choice. Consequently this field has revived the interest in techniques like operator splittings or augmented Lagrangians. Here we shall provide an overview of methods currently developed and recent results as well as some computational studies providing a comparison of different methods and also illustrating their success in applications.Comment: 60 pages, 33 figure

Event Processing through naming: Investigating event focus in two people with aphasia

Some people with aphasia may have trouble with verbs because of fundamental difficulties in processing situations in a way that maps readily onto language. This paper describes a novel assessment, the Order of Naming Test, that explores the conceptual processing of events through the order in which people name the entities involved. The performance of non-brain damaged control participants is described. The responses of two people with non-fluent aphasia are then discussed. Both 'Helen' and 'Ron' showed significant difficulty with verbs and sentences. Ron also had trouble on a range of tasks tapping aspects of event processing, despite intact non-verbal cognition. While Helen's performance on the Order of Naming Test was very similar to the controls, Ron's differed in a number of respects, suggesting that he was less focused on the main participant entities. However, certain aspects of his response pointed at covert event processing abilities that might be fruitfully exploited in therapy

An automatic technique for visual quality classification for MPEG-1 video

The Centre for Digital Video Processing at Dublin City University developed Fischlar [1], a web-based system for recording, analysis, browsing and playback of digitally captured television programs. One major issue for Fischlar is the automatic evaluation of video quality in order to avoid processing and storage of corrupted data. In this paper we propose an automatic classification technique that detects the video content quality in order to provide a decision criterion for the processing and storage stages

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes