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 series of experiments is reported in which subjects describe simple visual scenes by means of both sentential and non-sentential responses. The data support the following statements about the lexicalization (word finding) process. (1) Words used by speakers in overt naming or sentence production responses are selected by a sequence of two lexical retrieval processes, the first yielding abstract pre-phonological items (Ll -items), the second one adding their phonological shapes (L2-items). (2) The selection of several Ll-items for a multi-word utterance can take place simultaneously. (3) A monitoring process is watching the output of Ll-lexicalization to check if it is in keeping with prevailing constraints upon utterance format. (4) Retrieval of the L2-item which corresponds with a given LI-item waits until the Ld-item has been checked by the monitor, and all other Ll-items needed for the utterance under construction have become available. A coherent picture of the lexicalization process begins to emerge when these characteristics are brought together with other empirical results in the area of naming and sentence production, e.g., picture naming reaction times (Seymour, 1979), speech errors (Garrett, 1980), and word order preferences (Bock, 1982).