20,227 research outputs found

    Augmenting Situated Spoken Language Interaction with Listener Gaze

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    Collaborative task solving in a shared environment requires referential success. Human speakers follow the listener’s behavior in order to monitor language comprehension (Clark, 1996). Furthermore, a natural language generation (NLG) system can exploit listener gaze to realize an effective interaction strategy by responding to it with verbal feedback in virtual environments (Garoufi, Staudte, Koller, & Crocker, 2016). We augment situated spoken language interaction with listener gaze and investigate its role in human-human and human-machine interactions. Firstly, we evaluate its impact on prediction of reference resolution using a mulitimodal corpus collection from virtual environments. Secondly, we explore if and how a human speaker uses listener gaze in an indoor guidance task, while spontaneously referring to real-world objects in a real environment. Thirdly, we consider an object identification task for assembly under system instruction. We developed a multimodal interactive system and two NLG systems that integrate listener gaze in the generation mechanisms. The NLG system “Feedback” reacts to gaze with verbal feedback, either underspecified or contrastive. The NLG system “Installments” uses gaze to incrementally refer to an object in the form of installments. Our results showed that gaze features improved the accuracy of automatic prediction of reference resolution. Further, we found that human speakers are very good at producing referring expressions, and showing listener gaze did not improve performance, but elicited more negative feedback. In contrast, we showed that an NLG system that exploits listener gaze benefits the listener’s understanding. Specifically, combining a short, ambiguous instruction with con- trastive feedback resulted in faster interactions compared to underspecified feedback, and even outperformed following long, unambiguous instructions. Moreover, alternating the underspecified and contrastive responses in an interleaved manner led to better engagement with the system and an effcient information uptake, and resulted in equally good performance. Somewhat surprisingly, when gaze was incorporated more indirectly in the generation procedure and used to trigger installments, the non-interactive approach that outputs an instruction all at once was more effective. However, if the spatial expression was mentioned first, referring in gaze-driven installments was as efficient as following an exhaustive instruction. In sum, we provide a proof of concept that listener gaze can effectively be used in situated human-machine interaction. An assistance system using gaze cues is more attentive and adapts to listener behavior to ensure communicative success

    Focusing for Pronoun Resolution in English Discourse: An Implementation

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    Anaphora resolution is one of the most active research areas in natural language processing. This study examines focusing as a tool for the resolution of pronouns which are a kind of anaphora. Focusing is a discourse phenomenon like anaphora. Candy Sidner formalized focusing in her 1979 MIT PhD thesis and devised several algorithms to resolve definite anaphora including pronouns. She presented her theory in a computational framework but did not generally implement the algorithms. Her algorithms related to focusing and pronoun resolution are implemented in this thesis. This implementation provides a better comprehension of the theory both from a conceptual and a computational point of view. The resulting program is tested on different discourse segments, and evaluation and analysis of the experiments are presented together with the statistical results.Comment: iii + 49 pages, compressed, uuencoded Postscript file; revised version of the first author's Bilkent M.S. thesis, written under the supervision of the second author; notify Akman via e-mail ([email protected]) or fax (+90-312-266-4126) if you are unable to obtain hardcopy, he'll work out somethin

    Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

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    This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

    Analysis of rotor vibratory loads using higher harmonic pitch control

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    Experimental studies of isolated rotors in forward flight have indicated that higher harmonic pitch control can reduce rotor noise. These tests also show that such pitch inputs can generate substantial vibratory loads. The modification is summarized of the RotorCRAFT (Computation of Rotor Aerodynamics in Forward flighT) analysis of isolated rotors to study the vibratory loading generated by high frequency pitch inputs. The original RotorCRAFT code was developed for use in the computation of such loading, and uses a highly refined rotor wake model to facilitate this task. The extended version of RotorCRAFT incorporates a variety of new features including: arbitrary periodic root pitch control; computation of blade stresses and hub loads; improved modeling of near wake unsteady effects; and preliminary implementation of a coupled prediction of rotor airloads and noise. Correlation studies are carried out with existing blade stress and vibratory hub load data to assess the performance of the extended code
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