5,174 research outputs found

    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

    Directional adposition use in English, Swedish and Finnish

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    Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo

    Computational Understanding, Generation and Evaluation of Creative Expressions

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    Computational creativity has received a good amount of research interest in generating creative artefacts programmatically. At the same time, research has been conducted in computational aesthetics, which essentially tries to analyse creativity exhibited in art. This thesis aims to unite these two distinct lines of research in the context of natural language generation by building, from models for interpretation and generation, a cohesive whole that can assess its own generations. I present a novel method for interpreting one of the most difficult rhetoric devices in the figurative use of language: metaphors. The method does not rely on hand-annotated data and it is purely data-driven. It obtains the state of the art results and is comparable to the interpretations given by humans. We show how a metaphor interpretation model can be used in generating metaphors and metaphorical expressions. Furthermore, as a creative natural language generation task, we demonstrate assigning creative names to colours using an algorithmic approach that leverages a knowledge base of stereotypical associations for colours. Colour names produced by the approach were favoured by human judges to names given by humans 70% of the time. A genetic algorithm-based method is elaborated for slogan generation. The use of a genetic algorithm makes it possible to model the generation of text while optimising multiple fitness functions, as part of the evolutionary process, to assess the aesthetic quality of the output. Our evaluation indicates that having multiple balanced aesthetics outperforms a single maximised aesthetic. From an interplay of neural networks and the traditional AI approach of genetic algorithms, we present a symbiotic framework. This is called the master-apprentice framework. This makes it possible for the system to produce more diverse output as the neural network can learn from both the genetic algorithm and real people. The master-apprentice framework emphasises a strong theoretical foundation for the creative problem one seeks to solve. From this theoretical foundation, a reasoned evaluation method can be derived. This thesis presents two different evaluation practices based on two different theories on computational creativity. This research is conducted in two distinct practical tasks: pun generation in English and poetry generation in Finnish.Laskennallista luovuutta on tutkittu paljon puhtaan tuottamisen nÀkökulmasta ja saman aikaan tutkimusta on tehty laskennallisen estetiikan saralla. VÀitöskirjani yhdistÀÀ nÀitÀ kahta eri koulukuntaa, sillÀ kehittÀmÀni laskennallisesti luovat jÀrjestelmÀt kÀyttÀvÀt tuottamisessa apuna estetiikkaa; jÀrjestelmÀt siis tulkitsevat teoksiaan samaan aikaan, kun ne niitÀ tuottavat. KÀsittelen vÀitöskirjassani metaforien automaattista tulkintaa, vÀrien nimien tuottamista, sloganien tuottamista sekÀ suomenkielisen runouden tuottamista. Metodeina kÀytÀn perinteistÀ koneoppimisalgoritmia, eli niin kutsuttua geneettistÀ algoritmia, sekÀ neuroverkkoja. Niiden yhdistelmÀÀ nimitÀn mestari ja oppipoika -malliksi, jossa geneettinen algoritmi opettaa neuroverkkoja

    Conducting Online Focus Groups - Practical Advice for Information Systems Researchers

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    Video-based online focus groups (OFGs) present an emerging opportunity for Information Systems (IS) researchers to circumvent spatial and temporal constraints in collecting rich data. They enable researchers to overcome interpersonal and operational challenges arising from face-to-face (F2F) focus groups (FGs) by allowing participants, who are located anywhere in the world, to share their personal experiences from behind their screens. However, the realization of the full potential of OFGs for IS research is currently hampered by challenges and uncertainty over best practices when conducting such FGs. Consequently, we offer a detailed account of our own experiences with seven OFGs in the context of digital platforms. In supplementing our own experiences with those of others reported in extant literature on (online) FGs in and beyond the IS discipline, we (a) arrive at hurdles inherent to the OFG method, (b) derive lessons learned from our own experience with OFGs, and (c) prescribe actionable advice to researchers who are interested in conducting OFGs in the future

    What matters to older people with assisted living needs? A phenomenological analysis of the use and non-use of telehealth and telecare

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    Telehealth and telecare research has been dominated by efficacy trials. The field lacks a sophisticated theorisation of [a] what matters to older people with assisted living needs; [b] how illness affects people's capacity to use technologies; and [c] the materiality of assistive technologies. We sought to develop a phenomenologically and socio-materially informed theoretical model of assistive technology use. Forty people aged 60–98 (recruited via NHS, social care and third sector) were visited at home several times in 2011–13. Using ethnographic methods, we built a detailed picture of participants' lives, illness experiences and use (or non-use) of technologies. Data were analysed phenomenologically, drawing on the work of Heidegger, and contextualised using a structuration approach with reference to Bourdieu's notions of habitus and field. We found that participants' needs were diverse and unique. Each had multiple, mutually reinforcing impairments (e.g. tremor and visual loss and stiff hands) that were steadily worsening, culturally framed and bound up with the prospect of decline and death. They managed these conditions subjectively and experientially, appropriating or adapting technologies so as to enhance their capacity to sense and act on their world. Installed assistive technologies met few participants' needs; some devices had been abandoned and a few deliberately disabled. Successful technology arrangements were often characterised by ‘bricolage’ (pragmatic customisation, combining new with legacy devices) by the participant or someone who knew and cared about them. With few exceptions, the current generation of so-called ‘assisted living technologies’ does not assist people to live with illness. To overcome this irony, technology providers need to move beyond the goal of representing technology users informationally (e.g. as biometric data) to providing flexible components from which individuals and their carers can ‘think with things’ to improve the situated, lived experience of multi-morbidity. A radical revision of assistive technology design policy may be needed
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