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

Grammatical encoding and grammatical decoding (in sentence production and comprehension, respectively) are often portrayed as independent modalities of grammatical performance that only share declarative resources: lexicon and grammar. The processing resources subserving these modalities are supposed to be distinct. In particular, one assumes the existence of two workspaces where grammatical structures are assembled and temporarily maintained—one for each modality. An alternative theory holds that the two modalities share many of their processing resources and postulates a single mechanism for the online assemblage and short-term storage of grammatical structures: a shared workspace. We report two experiments with a novel “grammatical multitasking” paradigm: the participants had to read (i.e., decode) and to paraphrase (encode) sentences presented in fragments, responding to each input fragment as fast as possible with a fragment of the paraphrase. The main finding was that grammatical constraints with respect to upcoming input that emanate from decoded sentence fragments are immediately replaced by grammatical expectations emanating from the structure of the corresponding paraphrase fragments. This evidences that the two modalities have direct access to, and operate upon, the same (i.e., token-identical) grammatical structures. This is possible only if the grammatical encoding and decoding processes command the same, shared grammatical workspace. Theoretical implications for important forms of grammatical multitasking—self-monitoring, turn-taking in dialogue, speech shadowing, and simultaneous translation—are explored.

Abstract

Students who are learning to write in a foreign language, often want feedback on the grammatical quality of the sentences they produce. The usual NLP approach to this problem is based on parsing student-generated text. Here, we propose a generation-based ap- proach aiming at preventing errors ("scaffolding"). In our ICALL system, the student constructs sentences by composing syntactic trees out of lexically anchored "treelets" via a graphical drag & drop user interface. A natural-language generator computes all possible grammatically well-formed sentences entailed by the student-composed tree. It provides positive feedback if the student-composed tree belongs to the well-formed set, and negative feedback otherwise. If so requested by the student, it can substantiate the positive or negative feedback based on a comparison between the student-composed tree and its own trees (informative feedback on demand). In case of negative feedback, the system refuses to build the structure attempted by the student. Frequently occurring errors are handled in terms of "malrules." The system we describe is a prototype (implemented in JAVA and C++) which can be parameterized with respect to L1 and L2, the size of the lexicon, and the level of detail of the visually presented grammatical structures.