Publications

Abstract

In Dutch and German, the canonical order of subject, object(s) and finite verb is ‘verb-second’ (V2) in main but ‘verb-final’ (VF) in subordinate clauses. This occasionally leads to the production of noncanonical word orders. Familiar examples are causative and argumentative clauses introduced by a subordinating conjunction (Du. omdat, Ger. weil ‘because’): the omdat/weil-V2 phenomenon. Such clauses may also be introduced by coordinating conjunctions (Du. want, Ger. denn), which license V2 exclusively. However, want/denn-VF structures are unknown. We present the results of a corpus study on the incidence of omdat-V2 in spoken Dutch, and compare them to published data on weil-V2 in spoken German. Basic findings: omdat-V2 is much less frequent than weil-V2 (ratio almost 1:8); and the frequency relations between coordinating and subordinating conjunctions are opposite (want >> omdat; denn << weil). We propose that conjunction selection and V2/VF selection proceed partly independently, and sometimes miscommunicate—e.g. yielding omdat/weil paired with V2. Want/denn-VF pairs do not occur because want/denn clauses are planned as autonomous sentences, which take V2 by default. We sketch a simple feedforward neural network with two layers of nodes (representing conjunctions and word orders, respectively) that can simulate the observed data pattern through inhibition-based competition of the alternative choices within the node layers.

Abstract

The syntactic structure of main and subordinate clauses is determined to a considerable extent by verb biases. For example, some English and Dutch ditransitive verbs have a preference for the prepositional object dative, whereas others are typically used with the double object dative. In this study, we compare the effect of these biases on structure selection in (S)VO and (S)OV dative clauses in the Corpus of Spoken Dutch (CGN). This comparison allowed us to make inferences about the size of the advance planning scope during spontaneous speaking: If the verb is an obligatory component of clause-level advance planning scope, as is claimed by the hypothesis of hierarchical incrementality, then biases should exert their influence on structure choices, regardless of early (VO) or late (OV) position of the verb in the clause. Conversely, if planning proceeds in a piecemeal fashion, strictly guided by lexical availability, as claimed by linear incrementality, then the verb and its associated biases can only influence structure choices in VO sentences. We tested these predictions by analyzing structure choices in the CGN, using mixed logit models. Our results support a combination of linear and hierarchical incrementality, showing a significant influence of verb bias on structure choices in VO, and a weaker (but still significant) effect in OV clauses

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.