Publications

Abstract

In a paper entitled “Against markedness (and what to replace it with)”, Haspelmath argues “that the term ‘markedness’ is superfluous”, and that frequency asymmetries often explain structural (un)markedness asymmetries (Haspelmath 2006). We investigate whether this argument applies to Object and Verb orders in main (VO, marked) and subordinate (OV, unmarked) clauses of spoken and written German and Dutch, using English (without VO/OV alternation) as control. Frequency counts from six treebanks (three languages, two output modalities) do not support Haspelmath’s proposal. However, they reveal an unexpected phenomenon, most prominently in spoken Dutch and German: a small set of extremely high-frequent finite verbs with unspecific meanings populates main clauses much more densely than subordinate clauses. We suggest these verbs accelerate the start-up of grammatical encoding, thus facilitating sentence-initial output fluency

Abstract

In this exploratory study we test the hypothesis that the retrieval from memory of proper noun Agents (PNAs) under processing pressure causes a greater proportion of such semantic arguments to be placed to the right of the initial position in a clause than would be the case if such retrieval from memory were not necessary. This effect is manifest in sports commentary. Processing pressure on sports commentators is modulated by the speed at which the sport is played and reported. Non-initial placement is also facilitated by formulae which have slots in non-initial position. It follows that the non-initial placement of PNAs is not always semantically or pragmatically motivated. This finding therefore runs counter to a strong form of the functionalist hypothesis that syntactic choices available in the systemic structure of the syntax of a language offer solely semantic or pragmatic choices. It is an open question in a weak functionalist account of language and language use how processing and communicative functions interact in general.

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.