14,884 research outputs found
Natural language processing
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
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
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 tecnologÃas 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 lingüÃstica
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
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
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
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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