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Everyday conversation requires listeners to quickly recognize verbal actions, so-called speech acts, from the underspecified linguistic code and prepare a relevant response within the tight time const...
The use of virtual reality (VR) as a methodological tool is becoming increasingly popular in behavioral research as its flexibility allows for a wide range of applications. This new method has not bee...
为促进海峡两岸统计学科交流发展,建立高水平的统计学成果展示平台,给予两岸青年学者更多锻炼与学习的机会,由北京大学光华管理学院主办的第四届海峡两岸经济计量和环境统计交流与对话(Cross-Strait Dialogue IV)将于4月10日在光华2号楼K02教室举行。届时来自台湾中央研究院经济研究所的简锦汉所长带领学者团队,将再次走进北大燕园,与光华管理学院商务统计与经济计量系的师生们共聚一堂,就当...
Several attempts and case studies had been conducted to document the cultural heritage using the 3D Laser scanner in the last few years. Now, it is possible to furnish a virtual model of an object fro...
Most previous work on trainable language generation has focused on two paradigms: (a) using a generation decisions of an existing generator. Both approaches rely on the existence of a handcrafted gene...
We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can l...
Affirmative Cue Words in Task-Oriented Dialogue     Task-Oriented Dialogue  Cue Words       font style='font-size:12px;'> 2015/9/10
We present a series of studies of affirmative cue words—a family of cue words such as “okay” or “alright" that speakers use frequently in conversation. These words pose a challenge for spoken ...
In this article we focus on human–human multi-tasking dialogues, in which pairs of conversants, using speech, work on an ongoing task while occasionally completing real-time tasks. The ongoing task i...
We present a new data-driven methodology for simulation-based dialogue strategy learning, which allows us to address several problems in the field of automatic optimization of dialogue strateg...
We propose a method for learning dialogue management policies from a fixed data set. The method addresses the challenges posed by Information State Update (ISU)-based dialogue systems, which r...
In this article we use well-known machine learning methods to tackle a novel task, namely the classification of non-sentential utterances (NSUs) in dialogue. We introduce a fine-grained ...
This article focuses on the analysis and prediction of corrections, defined as turns where a user tries to correct a prior error made by a spoken dialogue system. We describe our labeling procedure of...
Building Coherence and Cohesion by Maite Taboada presents a detailed account olected aspects of the discourse of scheduling dialogs, which are conversations between two people trying to arrange a mee...
Evaluating Discourse and Dialogue Coding Schemes     Evaluating Discourse  Dialogue Coding Schemes       font style='font-size:12px;'> 2015/8/31
Agreement statistics play an important role in the evaluation of coding schemes for discourse and dialogue. Unfortunately there is a lack of understanding regarding appropriate agreement measures and ...
The problem of pragmatics arises as soon as we move beyond the linguistic analysis of an utterance and ask what the speaker meant by it. Now, speaker’s meaning is a particular case of intention, and a...

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