Publications

Abstract

It is an important feature of the human sentence production system that semantic and syntactic processes may overlap in time and do not proceed strictly serially. That is, the process of building the syntactic form of an utterance does not always wait until the complete semantic content for that utterance has been decided upon. On the contrary, speakers will often start pronouncing the first words of a sentence while still working on further details of its semantic content. An important advantage is memory economy. Semantic and syntactic fragments do not have to occupy working memory until complete semantic and syntactic structures for an utterance have been computed. Instead, each semantic and syntactic fragment is processed as soon as possible and is kept in working memory for a minimum period of time. This raises the question of how the sentence production system can maintain syntactic coherence across syntactic fragments. Presumably there are processes of "syntactic bookkeeping" which (1) store in working memory those syntactic properties of a fragmentary sentence which are needed to eliminate ungrammatical continuations, and (2) check whether a prospective continuation is indeed compatible with the sentence constructed so far. In reaction time experiments where subjects described, under time pressure, simple static pictures of an action performed by an actor, the second aspect of syntactic bookkeeping could be demonstrated. This evidence is used for modelling bookkeeping processes as part of a computational sentence generator which aims at simulating the syntactic operations people carry out during spontaneous speech.

Abstract

We outline an algorithm capable of generating varied but natural sounding sequences of argument NPs in subordinate clauses of German, a semi-free word order language. In order to attain the right level of output flexibility, the algorithm considers (1) the relevant lexical properties of the head verb (not only transitivity type but also reflexivity, thematic relations expressed by the NPs, etc.), and (2) the animacy and definiteness values of the arguments, and their length. The relevant statistical data were extracted from the NEGRA–II treebank and from hand-coded features for animacy and definiteness. The algorithm maps the relevant properties onto “primary” versus “secondary” placement options in the generator. The algorithm is restricted in that it does not take into account linear order determinants related to the sentence’s information structure and its discourse context (e.g. contrastiveness). These factors may modulate the above preferences or license “tertiary” linear orders beyond the primary and secondary options considered here.

Abstract

Recent research suggests that 12-month-old infants in German cultural settings have the motive of sharing their attention to and interest in various events with a social interlocutor. To do so, these preverbal infants predominantly use the pointing gesture (in this case the extended arm with or without extended index finger) as a means to direct another person’s attention. This task systematically investigates different types of motives underlying infants’ pointing. The occurrence of a protodeclarative (as opposed to protoimperative) motive is of particular interest because it requires an understanding of the recipient’s psychological states, such as attention and interest, that can be directed and accessed.

Abstract

There are three main strands of research which have investigated people’s intuitive knowledge of objects in motion. (1) Knowledge of the trajectories of objects in motion; (2) knowledge of the causes of motion; and (3) the categorisation of motion as to whether it has been produced by something animate or inanimate. We provide a brief introduction to each of these areas. We then point to some linguistic and cultural differences which may have consequences for people’s knowledge of objects in motion. Finally, we describe two experimental tasks and an ethnographic task that will allow us to collect data in order to establish whether, indeed, there are interesting cross-linguistic/cross-cultural differences in lay theories of objects in motion.

Abstract

Effekte linguisticher Typologie auf die Sprach-entwicklung. In G. Plehn (Ed.), Jahrbuch der Max-Planck Gesellsch

Abstract

The human language processor is conceived as a system that consists of several interrelated subsystems. Each subsystem performs a specific task in the complex process of language comprehension and production. A subsystem receives a particular input, performs certain specific operations on this input and yields a particular output. The subsystems can be characterized in terms of the transformations that relate the input representations to the output representations. An important issue in describing the language processing system is to identify the subsystems and to specify the relations between the subsystems. These relations can be conceived in two different ways. In one conception the subsystems are autonomous. They are related to each other only by the input-output channels. The operations in one subsystem are not affected by another system. The subsystems are modular, that is they are independent. In the other conception, the different subsystems influence each other. A subsystem affects the processes in another subsystem. In this conception there is an interaction between the subsystems.

Abstract

Although humans are the ultimate “natural language generators”, the area of psycholinguistic modeling has been somewhat underrepresented in recent approaches to Natural Language Generation in computer science. To draw attention to the area and illustrate its potential relevance to Natural Language Generation, I provide an overview of recent work on psycholinguistic modeling of language production together with some key empirical findings, state-of-the-art experimental techniques, and their historical roots. The techniques include analyses of speech-error corpora, chronometric analyses, eyetracking, and neuroimaging.
The overview is built around the issue of cognitive control in natural language generation, concentrating on the production of single words, which is an essential ingredient of the generation of larger utterances. Most of the work exploited the fact that human speakers are good but not perfect at resisting temptation, which has provided some critical clues about the nature of the underlying system.

Abstract

Listeners’ signals of recipiency, such as “Mm-hm” or “uh-huh” in English, are the most elementary or minimal “conversational turns” possible. Minimal, because apart from acknowledging recipiency and inviting the speaker to continue with his/her next turn, they do not add any new information to the discourse of the conversation. The goal of this project is to gather cross cultural information on listeners’ feedback behaviour during conversation. Listeners in a conversation usually provide short signals that indicate to the speaker that they are still “with the speaker”. These signals could be verbal (like for instance “mm hm” in English or “hm hm” in Dutch) or nonverbal (visual), like nodding. Often, these signals are produced in overlap with the speaker’s vocalisation. If listeners do not produce these signals, speakers often invite them explicitly (e.g. “are you still there?” in a telephone conversation). Our goal is to investigate what kind of signals are used by listeners of different languages to signal “recipiency” to the speaker.

Abstract

The basic idea behind this task is to find out how languages encode basic shape distinctions such as dimensionality, axial geometry, relative size, etc. More specifically, we want to find out (i) which formal means are used cross linguistically to encode basic shape distinctions, and (ii) which are the semantic distinctions that are made in this domain. In languages with many shape-classifiers, these distinctions are encoded (at least partially) in classifiers. In other languages, positional verbs, descriptive modifiers, such as “flat”, “round”, or nouns such as “cube”, “ball”, etc. might be the preferred means. In this context, we also want to investigate what other “grammatical work” shapeencoding expressions possibly do in a given language, e.g. unitization of mass nouns, or anaphoric uses of shape-encoding classifiers, etc. This task further seeks to determine the role of shape-related parameters which underlie the design of objects in the semantics of the system under investigation.