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This thesis describes work in three areas: grammar engineering, computer-assisted language learning and grammar learning. These three parts are connected by the concept of a grammar-based language learning application. Two types of grammars are of concern. The first we call resource grammars, extensive descriptions a natural languages. Part I focuses on this kind of grammars. The other are domain-specific or application-specific grammars. These grammars only describe a fragment of natural language that is determined by the domain of a certain application. Domain-specific grammars are relevant for Part II and Part III. Another important distinction is between humans learning a new natural language using computational grammars (Part II) and computers learning grammars from example sentences (Part III). Part I of this thesis focuses on grammar engineering and grammar testing. It describes the development and evaluation of a computational resource grammar for Latin. Latin is known for its rich morphology and free word order, both have to be handled in a computationally efficient way. A special focus is on methods how computational grammars can be evaluated using corpus data. Such an evaluation is presented for the Latin resource grammar. Part II, the central part, describes a computer-assisted language learning application based on domain-specific grammars. The language learning application demonstrates how computational grammars can be used to guide the user input and how language learning exercises can be modeled as grammars. This allows us to put computational grammars in the center of the design of language learning exercises used to help humans learn new languages. Part III, the final part, is dedicated to a method to learn domain- or application-specific grammars based on a wide-coverage grammar and small sets of example sentences. Here a computer is learning a grammar for a fragment of a natural language from example sentences, potentially without any additional human intervention. These learned grammars can be based e.g. on the Latin resource grammar described in Part II and used as domain-specific lesson grammars in the language learning application described Part II.
When humans have a conversation with one-another, they generally take turns speaking one after the other without overlapping each others talk or leaving silence between turns for long stretches of time. Previous research has shown that conversation is a structured practice following rules that help interlocutors to manage the flow of conversation interactively. While at the beginning of a conversation it remains open who will speak when about what and for how long, interlocutors regulate the flow of conversation as it unfolds. One basic set of rules that interlocutors operate with governs the allocation of speaking turns, with the central rule stating that whoever starts speaking first at a point in time when speaker change becomes relevant has the rights and obligations to produce the next turn. The organization of turn allocation, therefore, is one reason for conversational turn taking to be so remarkably fast, with the beginnings of turns most often being quite accurately aligned with the ends of the previous turns. Observations of this outstanding speed of turn taking gave rise to a number of questions concerning language processing in conversational situations. The studies presented in this thesis investigate some of these questions from the perspective of the current listener preparing to be the next speaker who will respond to the current turn.
The study presented in Chapter 2 investigates when next speakers begin to plan their own turn with respect to two points in time, (i) the moment when the incoming turn’s message becomes clear enough to make response planning possible and (ii) the moment when the incoming turn terminates. Results of previous studies were inconclusive about the timing of language planning in conversation, with evidence in favour of both late and early response planning. Furthermore, previous studies presented both evidence as well as counter evidence indicating that response planning depends or does not depend on an accurate prediction of the timing of the incoming turn’s end. The study presented here makes use of a novel experimental paradigm which includes a dialogic task that participants need to fulfil in response to critical utterances by a confederate. These critical utterances were structured, on the one hand, so that their message became clear either only at the end of the turn or before the end of the turn, and, on the other hand, so that it was either predictable or not predictable when exactly the turn would end. Participant’s eye-movements as well as their response latencies indicated that they always planned their next turn as early as possible, irrespective of the predictability of the incoming turn’s end. The presented results provide evidence in favour of models of turn taking that predict speech planning to happen in overlap with the incoming turn.
Having established that next speakers begin to plan their turn in overlap, the study presented in Chapter 3 goes more into detail investigating to which depth language planning progresses while the incoming turn is still unfolding. To this end, a number of psycholinguistic paradigms were combined. In the study’s main experiment, participants had to fulfil a switch-task in which they switched from picture naming in response to an auditorily presented question to making a lexical decision. By manipulating the relatedness of the word for lexical decision with the picture that was prepared to be named before the task-switch it was possible to draw inferences on which processing stages were entered during the speech production process in overlap with the incoming turn. Participants’ behavioural responses in the lexical decision task revealed that they entered the stage of phonological encoding while the incoming turn was still unfolding, showing that planning in overlap is not limited to conceptual preparation but includes all sub-processes of formulation.
Given that speech production regularly enters the stages of formulation in overlap with the incoming turn, as shown in Chapters 2 and 3, the question arises whether planning the next turn in overlap is cognitively more demanding than during the gap between turns. This question is approached in the study presented in Chapter 4 by measuring pupillometric responses of participants in a dialogic task. An increase in pupil diameter during a cognitive task is indicative of increased processing load, and pupillometric responses to planning in overlap with the incoming turn were found to be greater than responses to planning in the gap between turns. These results show that planning in overlap is more demanding than planning during the gap, even though it is highly practiced by speakers.
After Chapters 2 to 4 investigated the timing and mechanisms of speech planning in conversation, Chapter 5 turns towards the timing of articulation of a planned turn, asking the question what sources of information next speakers use to time the articulation of a planned utterance to start closely after the incoming turn comes to an end. In this Chapter’s study, participants taking turns with a confederate responded to utterances containing or not containing different cues to the location of the incoming turn’s end. Participants made use of lexical and turn-final intonational cues, but not of turn-initial intonational cues, responding faster when the relevant cues were present than when they were not present. These results show that the timing of turn initiation in next speakers depends on the recognition of the incoming turn’s point of completion and not merely on the progress in planning the next turn.
All evidence presented in Chapters 2 to 5 is summed up and bundled together in a cognitive model of turn taking, which is being presented in Chapter 6. This model assumes, centrally, that the planning of a turn and the timing of its articulation are separate cognitive processes that run in parallel in any next speaker during conversation. Planning generally starts as early as possible, often in overlap with the incoming turn, while the timing of articulation depends on the next speaker’s level of certainty that speaker change has become relevant at a particular moment, with a number of cues to the end of the incoming turn leading to an increase of certainty. Next turns are assumed to often be planned down to fully formulated utterance plans including their phonological form as early as possible on the basis of anticipations of the incoming turn’s message, which are created with the help of the general and situational knowledge about the world, the current speaker and her intentions, as well as the input that has been received so far. The level of certainty that speaker change becomes relevant rises or decreases as lexico-syntactic, prosodic, and pragmatic projections about the development of the current turn are fulfilled or not fulfilled. As the incoming turn progresses towards its end as was projected by the current listener, he becomes certain that speaker change becomes relevant and will initiate articulation of the prepared next turn. Viewing these two processes, planning a next turn and timing of its articulation, as separate makes it possible to explain the observable fast timing of turn taking while still modelling the allocation of turns as interactionally managed by interlocutors — a considerable advantage of the presented model compared to more traditional perspectives on turn taking and conversation.