The Many Functions of Discourse Particles: A Computational Model of Pragmatic Interpretation

We present a connectionist model for the interpretation of discourse\ud particles in real dialogues that is based on neuronal\ud principles of categorization (categorical perception, prototype\ud formation, contextual interpretation). It can be shown that\ud discourse particles operate just like other morphological and\ud lexical items with respect to interpretation processes. The description\ud proposed locates discourse particles in an elaborate\ud model of communication which incorporates many different\ud aspects of the communicative situation. We therefore also\ud attempt to explore the content of the category discourse particle.\ud We present a detailed analysis of the meaning assignment\ud problem and show that 80%– 90% correctness for unseen discourse\ud particles can be reached with the feature analysis provided.\ud Furthermore, we show that ‘analogical transfer’ from\ud one discourse particle to another is facilitated if prototypes\ud are computed and used as the basis for generalization. We\ud conclude that the interpretation processes which are a part of\ud the human cognitive system are very similar with respect to\ud different linguistic items. However, the analysis of discourse\ud particles shows clearly that any explanatory theory of language\ud needs to incorporate a theory of communication processes

Now what? First year student teachers' reflective journal writing.

With the increasing focus for New Zealand teachers on reflective practice, initial teacher educators must take increasing responsibility in scaffolding students' critical writing, developing reflection skills for working in schools, the teacher registration process and ongoing professional learning. This article reports a study of journal writing practices of a sample of student teachers in their first year of an undergraduate degree at the University of Waikato. Of particular interest in the findings are the sophistication of the students' writing, choice of topic for each entry and the impact of feedback and support provided

From Monologue to Dialogue: Natural Language Generation in OVIS

This paper describes how a language generation system that was originally designed for monologue generation, has been adapted for use in the OVIS spoken dialogue system. To meet the requirement that in a dialogue, the system's utterances should make up a single, coherent dialogue turn, several modifications had to be made to the system. The paper also discusses the influence of dialogue context on information status, and its consequences for the generation of referring expressions and accentuation

The process of minimising medicine use through dialogue based animal health and welfare planning, Workshop report FIBL. In: CORE Organic project no. 1903 - ANIPLAN

The process of minimising medicine use through dialogue based animal health and welfare planning. Livestock are important in many organic farming systems, and it is an explicit goal to ensure high levels of animal health and welfare (AHW) through good management. In two previous EU network projects, NAHWOA & SAFO, it was concluded that this is not guaranteed merely by following organic standards. Both networks recommended implementation of individual animal health plans to stimulate organic farmers to improve AHW. These plans should include a systematic evaluation of AHW and be implemented through dialogue with each farmer in order to identify goals and plan improvements. 11 research institutions in 7 European countries have been involved in the ANIPLAN project with the main objective to minimise medicine use in organic dairy herds through active and well planned AHW promotion and disease prevention. The project consisted of 5 work packages, 4 of which comprised research activities building on current research projects, new applications across borders, exchange of knowledge, results and conclusions between participating countries, and adopting them to widely different contexts. International and national workshops have facilitated this exchange. In the project, animal health and welfare planning principles for organic dairy farms under diverse conditions were developed. Animal health and welfare assessments, based on the WelfareQuality parameters, were conducted in different types of organic dairy herds across Europe. Finally, guidelines for communication about animal health and welfare promotion in different settings were also developed relevant to both existing animal health advisory services or farmer groups such as the Danish Stable School system and the Dutch network program. These proceedings contain the presentations at the final workshop, which also included invited external guests. The proceedings also contain three reports which are deliverables of the project. They are focused on the process of planning for better animal health and welfare, and how farmers and facilitators manage this situation. The focus areas are animal health planning, AHW assessment using animal based parameters and development of advisory systems and farmer groups

A generic architecture and dialogue model for multimodal interaction

This paper presents a generic architecture and a dialogue model for multimodal interaction. Architecture and model are transparent and have been used for different task domains. In this paper the emphasis is on their use for the navigation task in a virtual environment. The dialogue model is based on the information state approach and the recognition of dialogue acts. We explain how pairs of backward and forward looking tags and the preference rules of the dialogue act determiner together determine the structure of the dialogues that can be handled by the system. The system action selection mechanism and the problem of reference resolution are discussed in detail

A Personalized System for Conversational Recommendations

Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as movies or restaurants, but are still somewhat awkward to use. Our solution is to take advantage of the complementary strengths of personalized recommendation systems and dialogue systems, creating personalized aides. We present a system -- the Adaptive Place Advisor -- that treats item selection as an interactive, conversational process, with the program inquiring about item attributes and the user responding. Individual, long-term user preferences are unobtrusively obtained in the course of normal recommendation dialogues and used to direct future conversations with the same user. We present a novel user model that influences both item search and the questions asked during a conversation. We demonstrate the effectiveness of our system in significantly reducing the time and number of interactions required to find a satisfactory item, as compared to a control group of users interacting with a non-adaptive version of the system