Publications

Abstract

In present-day spoken German, subordinate clauses introduced by the connector weil ‘because’ occur with two orders of subject, finite verb, and object(s). In addition to weil clauses with verb-final word order (“VF”; standard in subordinate clauses) one often hears weil clauses with SVO, the standard order of main clauses (“verb-second”, V2). The “weil-V2” phenomenon is restricted to sentences where the weil clause follows the main clause, and is virtually absent from formal (written, edited) German, occurring only in extemporaneous speech. Extant accounts of weil-V2 focus on the interpretation of weil-V2 clauses by the hearer, in particular on the type of discourse relation licensed by weil-V2 vs. weil-VF: causal/propositional or inferential/epistemic. Focusing instead on the production of weil clauses by the speaker, we examine a collection of about 1,000 sentences featuring a causal connector (weil, da or denn) after the main clause, all extracted from a corpus of spoken German dialogues and annotated with tags denoting major prosodic and syntactic boundaries, and various types of disfluencies (pauses, hesitations). Based on the observed frequency patterns and on known linguistic properties of the connectors, we propose that weil-V2 is caused by miscoordination between the mechanisms for lexical retrieval and grammatical encoding: Due to its high frequency, the lexical item weil is often selected prematurely, while the grammatical encoder is still working on the syntactic shape of the weil clause. Weil-V2 arises when pragmatic and processing factors drive the encoder to discontinue the current sentence, and to plan the clause following weil in the form of the main clause of an independent, new sentence. Thus, the speaker continues with a V2 clause, seemingly in violation of the VF constraint imposed by the preceding weil. We also explore implications of the model regarding the interpretation of sentences containing causal connectors.

Abstract

The study develops a neurocomputational architecture for grammatical processing in language production and language comprehension (grammatical encoding and decoding, respectively). It seeks to answer two questions. First, how is online syntactic structure formation of the complexity required by natural-language grammars possible in a fixed, preexisting neural network without the need for online creation of new connections or associations? Second, is it realistic to assume that the seemingly disparate instantiations of syntactic structure formation in grammatical encoding and grammatical decoding can run on the same neural infrastructure? This issue is prompted by accumulating experimental evidence for the hypothesis that the mechanisms for grammatical decoding overlap with those for grammatical encoding to a considerable extent, thus inviting the hypothesis of a single “grammatical coder.” The paper answers both questions by providing the blueprint for a syntactic structure formation mechanism that is entirely based on prewired circuitry (except for referential processing, which relies on the rapid learning capacity of the hippocampal complex), and can subserve decoding as well as encoding tasks. The model builds on the “Unification Space” model of syntactic parsing developed by Vosse & Kempen (2000, 2008, 2009). The design includes a neurocomputational mechanism for the treatment of an important class of grammatical movement phenomena.

Abstract

A new cognitive architecture is proposed for the syntactic aspects of human sentence processing. The architecture, called Unification Space, is biologically inspired but not based on neural nets. Instead it relies on biosynthesis as a basic metaphor. We use simulated annealing as an optimization technique which searches for the best configuration of isolated syntactic segments or subtrees in the final parse tree. The gradually decaying activation of individual syntactic nodes determines the ‘global excitation level’ of the system. This parameter serves the function of ‘computational temperature’ in simulated annealing. We have built a computer implementation of the architecture which simulates well-known sentence understanding phenomena. We report successful simulations of the psycholinguistic effects of clause embedding, minimal attachment, right association and lexical ambiguity. In addition, we simulated impaired sentence understanding as observable in agrammatic patients. Since the Unification Space allows for contextual (semantic and pragmatic) influences on the syntactic tree formation process, it belongs to the class of interactive sentence processing models.