This report presents the initaitvies made by teachers in form of questions during four lessons in a highschool class. A class in senior highschool was filmed during six hours with four different teachers. The number of questions and other initiatives were counted. The dialogue was transcribed with CA regarding examples from questioning and dialogue. The study examined how many closed(open and rhetorical questions the teacher initiate. The initiatives from pupils in form of questions where also examined. The aim was to see whether or not there were any gender differences. The result show that the teacher dominate the classroom dialogue with more than 68% of the speech acts and that the closed questions still dominate the classroom. There were no gender differences in the total amount of classroomtime, but in the math session the boys dominated. Regarding initiatives from pupils there were no gender differences, but there were many comments and answers who were spoken out loud in the classroom without any order. The conclusion from this report is that the old patterns with the tacher domination in the classroom communication remains and that there are very few open questions which could benfit dialogue and democatic values.

Conventional synthetic voices can synthesise neutral read aloud speech well. But, to make synthetic speech more suitable for a wider range of applications, the voices need to express more than just the word identity. We need to develop voices that can partake in a conversation and express, e.g. agreement, disagreement, hesitation, in a natural and believable manner. In speech synthesis there are currently two dominating frameworks: unit selection and HMM-based speech synthesis. Both frameworks utilise recordings of human speech to build synthetic voices. Despite the fact that the content of the recordings determines the segmental and prosodic phenomena that can be synthesised, surprisingly little research has been made on utilising the corpus to extend the limited behaviour of conventional synthetic voices. In this thesis we will show how natural sounding conversational characteristics can be added to both unit selection and HMM-based synthetic voices, by adding speech from a spontaneous conversation to the voices. We recorded a spontaneous conversation, and by manually transcribing and selecting utterances we obtained approximately two thousand utterances from it. These conversational utterances were rich in conversational speech phenomena, but they lacked the general coverage that allows unit selection and HMM-based synthesis techniques to synthesise high quality speech. Therefore we investigated a number of blending approaches in the synthetic voices, where the conversational utterances were augmented with conventional read aloud speech. The synthetic voices that contained conversational speech were contrasted with conventional voices without conversational speech. The perceptual evaluations showed that the conversational voices were generally perceived by listeners as having a more conversational style than the conventional voices. This conversational style was largely due to the conversational voices’ ability to synthesise utterances that contained conversational speech phenomena in a more natural manner than the conventional voices. Additionally, we conducted an experiment that showed that natural sounding conversational characteristics in synthetic speech can convey pragmatic information, in our case an impression of certainty or uncertainty, about a topic to a listener. The conclusion drawn is that the limited behaviour of conventional synthetic voices can be enriched by utilising conversational speech in both unit selection and HMM-based speech synthesis.

This thesis is an inquiry into the nature and structure of face-to-face conversation, with a special focus on group meetings in the workplace. I argue that conversations are composed of episodes, each of which corresponds to an identifiable communicative activity such as giving instructions or telling a story. These activities are important because they are part of participants’ commonsense understanding of what happens in a conversation. They appear in natural summaries of conversations such as meeting minutes, and participants talk about them within the conversation itself. Episodic communicative activities therefore represent an essential component of practical, commonsense descriptions of conversations. The thesis objective is to provide a deeper understanding of how such activities may be recognized and differentiated from one another, and to develop a computational method for doing so automatically. The experiments are thus intended as initial steps toward future applications that will require analysis of such activities, such as an automatic minute-taker for workplace meetings, a browser for broadcast news archives, or an automatic decision mapper for planning interactions. My main theoretical contribution is to propose a novel analytical framework called participant relational analysis. The proposal argues that communicative activities are principally indicated through participant-relational features, i.e., expressions of relationships between participants and the dialogue. Participant-relational features, such as subjective language, verbal reference to the participants, and the distribution of speech activity amongst the participants, are therefore argued to be a principal means for analyzing the nature and structure of communicative activities. I then apply the proposed framework to two computational problems: automatic discourse segmentation and automatic discourse segment labeling. The first set of experiments test whether participant-relational features can serve as a basis for automatically segmenting conversations into discourse segments, e.g., activity episodes. Results show that they are effective across different levels of segmentation and different corpora, and indeed sometimes more effective than the commonly-used method of using semantic links between content words, i.e., lexical cohesion. They also show that feature performance is highly dependent on segment type, suggesting that human-annotated “topic segments” are in fact a multi-dimensional, heterogeneous collection of topic and activity-oriented units. Analysis of commonly used evaluation measures, performed in conjunction with the segmentation experiments, reveals that they fail to penalize substantially defective results due to inherent biases in the measures. I therefore preface the experiments with a comprehensive analysis of these biases and a proposal for a novel evaluation measure. A reevaluation of state-of-the-art segmentation algorithms using the novel measure produces substantially different results from previous studies. This raises serious questions about the effectiveness of some state-of-the-art algorithms and helps to identify the most appropriate ones to employ in the subsequent experiments. I also preface the experiments with an investigation of participant reference, an important type of participant-relational feature. I propose an annotation scheme with novel distinctions for vagueness, discourse function, and addressing-based referent inclusion, each of which are assessed for inter-coder reliability. The produced dataset includes annotations of 11,000 occasions of person-referring. The second set of experiments concern the use of participant-relational features to automatically identify labels for discourse segments. In contrast to assigning semantic topic labels, such as topical headlines, the proposed algorithm automatically labels segments according to activity type, e.g., presentation, discussion, and evaluation. The method is unsupervised and does not learn from annotated ground truth labels. Rather, it induces the labels through correlations between discourse segment boundaries and the occurrence of bracketing meta-discourse, i.e., occasions when the participants talk explicitly about what has just occurred or what is about to occur. Results show that bracketing meta-discourse is an effective basis for identifying some labels automatically, but that its use is limited if global correlations to segment features are not employed. This thesis addresses important pre-requisites to the automatic summarization of conversation. What I provide is a novel activity-oriented perspective on how summarization should be approached, and a novel participant-relational approach to conversational analysis. The experimental results show that analysis of participant-relational features is a.

This study offers a pragmatic account of verbal irony, arguing that verbal irony can be best treated as a special type of conversational implicature.As the first part of the thesis, Grice's theory of conversational implicature is revised. This is done by 1)an addition to Grice's Maxim of Quality so that this maxim will be able to take presupposition into account; 2)an inclusion of the notion of mutual knowledge in Grice's framework and 3)an establishment of speakers' motivation for violating Grice's Maxims. This motivation is subsumed into three principles--the Politeness Principle (PP) (following previous writers such as R. Lakoff, Brown and Levinson), which embodies the speaker's need and want to be polite to others, the Selfishness Principle (SP), which constrains the speaker to say things that will bring him/her desirable consequences, and the Expressivity Principle (EP), by observing which the speaker will succeed in leaving more propositional and emotional impact on the hearer. Lastly, a heuristic of implicature production and understanding is offered which is believed to be more coherent and explanatory than Grice's original procedures for implicature calculation.Second, the revised theory is applied to verbal irony. Based on the heuristic of implicature production and understanding, a heuristic of irony production and understanding is provided. This heuristic demonstrates that irony is both similar to and different from ordinary conversational implicatures. It is similar in that it results from the speaker's observance of the motivating principles, and thus violation of Grice's maxims. It is different because 1)It is seen as the violation of the Maxim of Quality alone, while in ordinary conversational implicatures, any of the maxims may be violated; and 2)This violation is caused by all the three motivating principles, the PP, the SP, and the EP, whereas an ordinary conversational implicature is usually motivated by one of these three principles. Finally, this heuristic is applied to various cases of verbal irony, showing that the revised theory of conversational implicature is better than previous proposals on the subjuct. / Department of English

Disputats, Stockholms universitet, 2008.

Trad. de : Diss. : Philos. Fak. : Düsseldorf : 1977, intitulée "Konversation : e. Kap. gesellschaftl. u. literar. Pragmatik im Frankreich d. 17. Jh." - Bibliogr. p. 287-307. -

Thesis (Ph. D.)--University of North Carolina at Greensboro, 1996. / Title from HTML title page (viewed on Apr. 19, 2010) Includes bibliographical references.

Thesis (M.S.L.P.)--Duquesne University, 2004. / Title from document title page. Abstract included in electronic submission form. Includes bibliographical references (p. 63-66) and index.

Thesis (Ph. D.)--UCLA, 2008. / Vita. Includes bibliographical references (leaves 494-503).

Thesis (M.Ed.)--University of Hong Kong, 1995. / Includes bibliographical references (leaves 87-89). Also available in print.