15,453 research outputs found
Individual and Domain Adaptation in Sentence Planning for Dialogue
One of the biggest challenges in the development and deployment of spoken
dialogue systems is the design of the spoken language generation module. This
challenge arises from the need for the generator to adapt to many features of
the dialogue domain, user population, and dialogue context. A promising
approach is trainable generation, which uses general-purpose linguistic
knowledge that is automatically adapted to the features of interest, such as
the application domain, individual user, or user group. In this paper we
present and evaluate a trainable sentence planner for providing restaurant
information in the MATCH dialogue system. We show that trainable sentence
planning can produce complex information presentations whose quality is
comparable to the output of a template-based generator tuned to this domain. We
also show that our method easily supports adapting the sentence planner to
individuals, and that the individualized sentence planners generally perform
better than models trained and tested on a population of individuals. Previous
work has documented and utilized individual preferences for content selection,
but to our knowledge, these results provide the first demonstration of
individual preferences for sentence planning operations, affecting the content
order, discourse structure and sentence structure of system responses. Finally,
we evaluate the contribution of different feature sets, and show that, in our
application, n-gram features often do as well as features based on higher-level
linguistic representations
Web and Semantic Web Query Languages
A number of techniques have been developed to facilitate
powerful data retrieval on the Web and Semantic Web. Three categories
of Web query languages can be distinguished, according to the format
of the data they can retrieve: XML, RDF and Topic Maps. This article
introduces the spectrum of languages falling into these categories
and summarises their salient aspects. The languages are introduced using
common sample data and query types. Key aspects of the query
languages considered are stressed in a conclusion
Generating Natural Language from Linked Data:Unsupervised template extraction
We propose an architecture for generating natural language from Linked Data that automatically learns sentence templates and statistical document planning from parallel RDF datasets and text. We have built a proof-of-concept system (LOD-DEF) trained on un-annotated text from the Simple English Wikipedia and RDF triples from DBpedia, focusing exclusively on factual, non-temporal information. The goal of the system is to generate short descriptions, equivalent to Wikipedia stubs, of entities found in Linked Datasets. We have evaluated the LOD-DEF system against a simple generate-from-triples baseline and human-generated output. In evaluation by humans, LOD-DEF significantly outperforms the baseline on two of three measures: non-redundancy and structure and coherence.
MELT - a Translated Domain Specific Language Embedded in the GCC Compiler
The GCC free compiler is a very large software, compiling source in several
languages for many targets on various systems. It can be extended by plugins,
which may take advantage of its power to provide extra specific functionality
(warnings, optimizations, source refactoring or navigation) by processing
various GCC internal representations (Gimple, Tree, ...). Writing plugins in C
is a complex and time-consuming task, but customizing GCC by using an existing
scripting language inside is impractical. We describe MELT, a specific
Lisp-like DSL which fits well into existing GCC technology and offers
high-level features (functional, object or reflexive programming, pattern
matching). MELT is translated to C fitted for GCC internals and provides
various features to facilitate this. This work shows that even huge, legacy,
software can be a posteriori extended by specifically tailored and translated
high-level DSLs.Comment: In Proceedings DSL 2011, arXiv:1109.032
GPU-based Streaming for Parallel Level of Detail on Massive Model Rendering
Rendering massive 3D models in real-time has long been recognized as a very challenging problem because of the limited computational power and memory space available in a workstation. Most existing rendering techniques, especially level of detail (LOD) processing, have suffered from their sequential execution natures, and does not scale well with the size of the models. We present a GPU-based progressive mesh simplification approach which enables the interactive rendering of large 3D models with hundreds of millions of triangles. Our work contributes to the massive rendering research in two ways. First, we develop a novel data structure to represent the progressive LOD mesh, and design a parallel mesh simplification algorithm towards GPU architecture. Second, we propose a GPU-based streaming approach which adopt a frame-to-frame coherence scheme in order to minimize the high communication cost between CPU and GPU. Our results show that the parallel mesh simplification algorithm and GPU-based streaming approach significantly improve the overall rendering performance
Patterns of grammaticalization in African languages
The approach outlined in the present paper is based on observations made with African languages. Although the 1000-odd African languages display a remarkable extent of structural variation, there are certain structures that do not seem to occur in Africa. Thus, to our knowledge, an African language having anything that could be called an ergative case or a numeral classifier system has not been discovered so far. It may turn out that our approach can, in a modified form, be made applicable to languages outside Africa. This , however, is a possibility that has not been considered here. The present approach is based essentially on diachronic findings in that it uses observations on language evolution in order to account for structural differences between languages. Thus, it has double potential: apart from describing and explaining typological diversity it can also be material to reconstructing language history
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