785,809 research outputs found
Proceedings of the Conference on Natural Language Processing 2010
This book contains state-of-the-art contributions to the 10th
conference on Natural Language Processing, KONVENS 2010
(Konferenz zur Verarbeitung natĂĽrlicher Sprache), with a focus
on semantic processing.
The KONVENS in general aims at offering a broad perspective
on current research and developments within the interdisciplinary
field of natural language processing. The central theme
draws specific attention towards addressing linguistic aspects
ofmeaning, covering deep as well as shallow approaches to semantic
processing. The contributions address both knowledgebased
and data-driven methods for modelling and acquiring
semantic information, and discuss the role of semantic information
in applications of language technology.
The articles demonstrate the importance of semantic processing,
and present novel and creative approaches to natural
language processing in general. Some contributions put their
focus on developing and improving NLP systems for tasks like
Named Entity Recognition or Word Sense Disambiguation, or
focus on semantic knowledge acquisition and exploitation with
respect to collaboratively built ressources, or harvesting semantic
information in virtual games. Others are set within the
context of real-world applications, such as Authoring Aids, Text
Summarisation and Information Retrieval. The collection highlights
the importance of semantic processing for different areas
and applications in Natural Language Processing, and provides
the reader with an overview of current research in this field
Recommended from our members
Evidence from neurolinguistic methodologies: can it actually inform linguistic/ language acquisition theories and translate to evidence-based applications?
This special issue is a testament to the recent burgeoning interest by theoretical linguists, language acquisitionists and teaching practitioners in the neuroscience of language. It offers a highly valuable, state-of-the-art overview of the neurophysiological methods that are currently being applied to questions in the field of second language (L2) acquisition, teaching and processing. Research in the area of neurolinguistics has developed dramatically in the past twenty years, providing a wealth of exciting findings, many of which are discussed in the papers in this volume. The goal of this commentary is twofold. The first is to critically assess the current state of neurolinguistic data from the point of view of language acquisition and processing—informed by the papers that comprise this special issue and the literature as a whole—pondering how the neuroscience of language/processing might inform us with respect to linguistic and language acquisition theories. The second goal is to offer some links from implications of exploring the first goal towards informing language teachers and the creation of linguistically and neurolinguistically-informed evidence-based pedagogies for non-native language teaching
Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering
Many vision and language tasks require commonsense reasoning beyond
data-driven image and natural language processing. Here we adopt Visual
Question Answering (VQA) as an example task, where a system is expected to
answer a question in natural language about an image. Current state-of-the-art
systems attempted to solve the task using deep neural architectures and
achieved promising performance. However, the resulting systems are generally
opaque and they struggle in understanding questions for which extra knowledge
is required. In this paper, we present an explicit reasoning layer on top of a
set of penultimate neural network based systems. The reasoning layer enables
reasoning and answering questions where additional knowledge is required, and
at the same time provides an interpretable interface to the end users.
Specifically, the reasoning layer adopts a Probabilistic Soft Logic (PSL) based
engine to reason over a basket of inputs: visual relations, the semantic parse
of the question, and background ontological knowledge from word2vec and
ConceptNet. Experimental analysis of the answers and the key evidential
predicates generated on the VQA dataset validate our approach.Comment: 9 pages, 3 figures, AAAI 201
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
Working memory capacity in L2 processing
In this paper, we review the current state of the second language (L2) processing literature and report data suggesting that this subfield should now turn its attention to working memory capacity as an important factor modulating the possibility of (near)-native-like L2 processing. We first review three major overarching accounts of L2 processing (Clahsen et al. 2006a, Grammatical processing in language learners. Applied Psycholinguistics 27. 3–42; Ullman 2001, The declarative/procedural model of lexicon and grammar. Journal of Psycholinguistic Research 30. 37–69; McDonald 2006, Beyond the critical period: Processing-based explanations for poor grammaticality judgment performance by late second language learners. Journal of Memory and Language 55. 381–401; Hopp 2006, Syntactic features and reanalysis in near-native processing. Second Language Research 22. 369–397, and Hopp 2010, Ultimate attainment in L2 inflection: Performance similarities between non-native and native speakers. Lingua 120. 901–931) and frame their predictions in terms of the qualitative and quantitative differences in processing expected between native speakers and L2 learners. We next review event-related potential (ERP) research on L2 processing and argue that the field’s current understanding of qualitative and quantitative differences in ERPs warrants an additional focus on variables other than L2 proficiency that can also predict individual differences in L2 processing. Recent L2 research (relying on ERPs, self-paced reading, and other online measures) suggests that the most promising such variable is working memory (WM) capacity. We summarize results from our recent L2 WM studies – and report new ERP findings – that point to the possibility of a modulatory effect of WM capacity on the nativelikeness of L2 processing. We conclude that the study of WM capacity is the logical next step for this L2 processing subfield
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