Flexible Natural Language Generation in Multiple Contexts

We present a practical approach to Natural Language Generation (NLG) for spoken dialogue systems. The approach is based on small template fragments (mini-templates). The system’s object architecture facilitates generation of phrases across pre-defined business domains and registers, as well as into different languages. The architecture simplifies NLG in well-understood application contexts, while providing the flexibility for a developer and for the system, to vary linguistic output according to dialogue context, including any intended affective impact. Mini-templates are used with a suite of domain term objects, resulting in an NLG system (MINTGEN – MINi-Template GENerator) whose extensibility and ease of maintenance is enhanced by the sparsity of information devoted to individual domains. The system also avoids the need for specialist linguistic competence on the part of the system maintainer.

Recognising Ecological Contexts of Diverse Ethnic Groups: Experiences of British-Indian Adult Children of Divorce

The process of divorce as a family change process including outcomes and consequences has received considerable research attention in the western context. However, the experience of divorce for children within specific ethnic contexts has been rather limited leading to poor planning and practice provision with diverse families. By drawing upon an empirical qualitative study of British Indian adult children, this paper will make a case for recognising diverse needs within specific historical, socio-cultural and developmental contexts. There is a need to acknowledge these contexts in policy design to establish practice that is flexible, accessible and relevant to the needs of different and diverse communities. Results indicate that areas of impact may be similar to those identified by other studies within the literature review. However, the experiences, expressions, implications and larger consequences of impact are located within specific socio-cultural contexts. In support of this, major findings of the study (outlined below) will be discussed - Context: patriarchy, stigma, immigration; Impact: economic, social, emotional, career/education, physical; Coping: psychological strategies, physical strategies, social strategies, sources of support.

When some is actually all: Scalar inferences in face-threatening contexts

Accounts of the scalar inference from 'some X-ed' to 'not all X-ed' are central to the debate between contemporary theories of conversational pragmatics. An important contribution to this debate is to identify contexts that decrease the endorsement rate of the inference. We suggest that the inference is endorsed less often in face-threatening contexts, i.e., when X implies a loss of face for the listener. This claim is successfully tested in Experiment 1. Experiment 2 rules out a possible confound between face-threatening contexts and lower-bound contexts. Experiment 3 shows that whilst saying 'some X-ed' when one knew for a fact that all X-ed is always perceived as an underinformative utterance, it is also seen as a nice and polite thing to do when X threatens the face of the listener. These findings are considered from the perspective of Relevance Theory as well as that of the Generalized Conversational Inference approach. (C) 2009 Elsevier B.V. All rights reserved.