62,916 research outputs found
Master Questions, Student Questions, and Genuine Questions: A Performative Analysis of Questions in Chan Encounter Dialogues
I want to know whether Chan masters and students depicted in classical Chan transmission literature can be interpreted as asking open (or what I will call “genuine”) questions. My task is significant because asking genuine questions appears to be a decisive factor in ascertaining whether these figures represent models for dialogue—the kind of dialogue championed in democratic society and valued by promoters of interreligious exchange. My study also contributes to a more comprehensive understanding of early Chan not only by detailing contrasts between contemporary interests and classical Chan, but more importantly by paying greater attention to the role language and rhetoric play in classical Chan. What roles do questions play in Chan encounter dialogues, and are any of the questions genuine? Is there anything about the conventions of the genre that keeps readers from interpreting some questions in this way? To address these topics, I will proceed as follows. First, on a global level and for critical-historical context, I survey Chan transmission literature of the Song dynasty in which encounter dialogues appear, and their role in developments of Chan/Zen traditions. Second, I zoom in on structural elements of encounter dialogues in particular as a genre. Third, aligning with the trajectory of performative analyses of Chan literature called for by Sharf and Faure, I turn to develop and criticize a performative model of questions from resources in recent analytic and continental philosophy of language and I apply that model to some questions in encounter dialogue literature
RRL: A Rich Representation Language for the Description of Agent Behaviour in NECA
In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is a formal framework for representing the information that is exchanged at the interfaces between the various NECA system modules
Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems
This paper presents the Frames dataset (Frames is available at
http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues
with an average of 15 turns per dialogue. We developed this dataset to study
the role of memory in goal-oriented dialogue systems. Based on Frames, we
introduce a task called frame tracking, which extends state tracking to a
setting where several states are tracked simultaneously. We propose a baseline
model for this task. We show that Frames can also be used to study memory in
dialogue management and information presentation through natural language
generation
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
Collaborating on Referring Expressions
This paper presents a computational model of how conversational participants
collaborate in order to make a referring action successful. The model is based
on the view of language as goal-directed behavior. We propose that the content
of a referring expression can be accounted for by the planning paradigm. Not
only does this approach allow the processes of building referring expressions
and identifying their referents to be captured by plan construction and plan
inference, it also allows us to account for how participants clarify a
referring expression by using meta-actions that reason about and manipulate the
plan derivation that corresponds to the referring expression. To account for
how clarification goals arise and how inferred clarification plans affect the
agent, we propose that the agents are in a certain state of mind, and that this
state includes an intention to achieve the goal of referring and a plan that
the agents are currently considering. It is this mental state that sanctions
the adoption of goals and the acceptance of inferred plans, and so acts as a
link between understanding and generation.Comment: 32 pages, 2 figures, to appear in Computation Linguistics 21-
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Reference and Gestures in Dialogue Generation: Three Studies with Embodied Conversational Agents
This paper reports on three studies into social presence cues which were carried out in the context of the NECA (Net-environment for Embodied Emotional Conversational Agents) project and the EPOCH network. The first study concerns the generation of referring expressions. We adopted an existing algorithm for generating referring expressions such that it could run according to an egocentric and a neutral strategy. In an evaluation study, we found that the two strategies were correlated with the perceived friendliness of the speaker. In the second and the third study, we evaluated the gestures that were generated by the NECA system. In this paper, we briefly summarize the most salient results of these two studies. They concern the effect of gestures on perceived quality of speech and information retention
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