14,884 research outputs found

    Natural language processing

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    Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

    Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation

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    With the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language models to understand human intent. Since these models require large amounts of data and in-domain knowledge, expanding an equivalent service into new markets is disrupted by language barriers that inhibit dialog automation. This paper presents a user study to evaluate the utility of out-of-the-box machine translation technology to (1) rapidly bootstrap multilingual spoken dialog systems and (2) enable existing human analysts to understand foreign language utterances. We additionally evaluate the utility of machine translation in human assisted environments, where a portion of the traffic is processed by analysts. In English->Spanish experiments, we observe a high potential for dialog automation, as well as the potential for human analysts to process foreign language utterances with high accuracy.Comment: 6 pages, 3 figures, accepted for publication at the 2018 European Association for Machine Translation Conference (EAMT 2018

    Marketing and Advertising Translation: Humans vs Machines in the field of cosmetics

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    This undergraduate thesis focuses on a very specific field of specialized translation: advertising and marketing translation. Indeed, the high degree of specialization involved in this activity provides a testing ground for a reconsideration of the importance of the human translator and a reformulation of their role. The constant development of new technologies creates ever more sophisticated translation programs, which in turn revives the long-standing machine vs human translation debate. The aim of this project is to conduct a practical exercise targeted at verifying whether specialization in translation always requires the supervision of humans equipped with the relevant linguistic knowledge and technical background, or whether, on the contrary, machine translation can at present provide valid enough results and a sufficient level of reliability.El presente Trabajo de Fin de Grado se centra en un campo muy concreto de la traducción especializada: la traducción para la publicidad y la mercadotecnia. De hecho, el alto grado de especialización que implica esta actividad proporciona un campo de pruebas para una reconsideración de la importancia del traductor humano y una reformulación de su papel. El desarrollo creciente e ininterrumpido de las nuevas tecnologías está produciendo programas de traducción cada vez más sofisticados, lo que a su vez reaviva el viejo debate que confronta la traducción humana y la traducción automática. El objetivo de este proyecto es llevar a cabo un ejercicio práctico destinado a verificar si la especialización en la traducción siempre requiere la supervisión de personas con la formación lingüística y los conocimientos técnicos pertinentes, o si, por el contrario, la traducción automática puede en la actualidad proporcionar por si sola resultados suficientes y un nivel suficiente de fiabilidad.Grado en Estudios Inglese

    Data analytics 2016: proceedings of the fifth international conference on data analytics

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    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

    Trialing project-based learning in a new EAP ESP course: A collaborative reflective practice of three college English teachers

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    Currently in many Chinese universities, the traditional College English course is facing the risk of being ‘marginalized’, replaced or even removed, and many hours previously allocated to the course are now being taken by EAP or ESP. At X University in northern China, a curriculum reform as such is taking place, as a result of which a new course has been created called ‘xue ke’ English. Despite the fact that ‘xue ke’ means subject literally, the course designer has made it clear that subject content is not the target, nor is the course the same as EAP or ESP. This curriculum initiative, while possibly having been justified with a rationale of some kind (e.g. to meet with changing social and/or academic needs of students and/or institutions), this is posing a great challenge for, as well as considerable pressure on, a number of College English teachers who have taught this single course for almost their entire teaching career. In such a context, three teachers formed a peer support group in Semester One this year, to work collaboratively co-tackling the challenge, and they chose Project-Based Learning (PBL) for the new course. This presentation will report on the implementation of this project, including the overall designing, operational procedure, and the teachers’ reflections. Based on discussion, pre-agreement was reached on the purpose and manner of collaboration as offering peer support for more effective teaching and learning and fulfilling and pleasant professional development. A WeChat group was set up as the chief platform for messaging, idea-sharing, and resource-exchanging. Physical meetings were supplementary, with sound agenda but flexible time, and venues. Mosoteach cloud class (lan mo yun ban ke) was established as a tool for virtual learning, employed both in and after class. Discussions were held at the beginning of the semester which determined only brief outlines for PBL implementation and allowed space for everyone to autonomously explore in their own way. Constant further discussions followed, which generated a great deal of opportunities for peer learning and lesson plan modifications. A reflective journal, in a greater or lesser detailed manner, was also kept by each teacher to record the journey of the collaboration. At the end of the semester, it was commonly recognized that, although challenges existed, the collaboration was overall a success and they were all willing to continue with it and endeavor to refine it to be a more professional and productive approach
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