134,995 research outputs found
Implementation of a Human-Computer Interface for Computer Assisted Translation and Handwritten Text Recognition
A human-computer interface is developed to provide services of computer assisted machine translation (CAT) and computer assisted transcription of handwritten text images (CATTI). The back-end machine translation (MT) and handwritten text recognition (HTR) systems are provided by the Pattern Recognition and Human Language Technology (PRHLT) research group. The idea is to provide users with easy to use tools to convert interactive translation and transcription feasible tasks. The assisted service is provided by remote servers with CAT or CATTI capabilities. The interface supplies the user with tools for efficient local edition: deletion, insertion and substitution.Ocampo SepĂșlveda, JC. (2009). Implementation of a Human-Computer Interface for Computer Assisted Translation and Handwritten Text Recognition. http://hdl.handle.net/10251/14318Archivo delegad
Considerations on command and response language features for a network of heterogeneous autonomous computers
The design of a uniform command language to be used in a local area network of heterogeneous, autonomous nodes is considered. After examining the major characteristics of such a network, and after considering the profile of a scientist using the computers on the net as an investigative aid, a set of reasonable requirements for the command language are derived. Taking into account the possible inefficiencies in implementing a guest-layered network operating system and command language on a heterogeneous net, the authors examine command language naming, process/procedure invocation, parameter acquisition, help and response facilities, and other features found in single-node command languages, and conclude that some features may extend simply to the network case, others extend after some restrictions are imposed, and still others require modifications. In addition, it is noted that some requirements considered reasonable (user accounting reports, for example) demand further study before they can be efficiently implemented on a network of the sort described
OpenCL Actors - Adding Data Parallelism to Actor-based Programming with CAF
The actor model of computation has been designed for a seamless support of
concurrency and distribution. However, it remains unspecific about data
parallel program flows, while available processing power of modern many core
hardware such as graphics processing units (GPUs) or coprocessors increases the
relevance of data parallelism for general-purpose computation.
In this work, we introduce OpenCL-enabled actors to the C++ Actor Framework
(CAF). This offers a high level interface for accessing any OpenCL device
without leaving the actor paradigm. The new type of actor is integrated into
the runtime environment of CAF and gives rise to transparent message passing in
distributed systems on heterogeneous hardware. Following the actor logic in
CAF, OpenCL kernels can be composed while encapsulated in C++ actors, hence
operate in a multi-stage fashion on data resident at the GPU. Developers are
thus enabled to build complex data parallel programs from primitives without
leaving the actor paradigm, nor sacrificing performance. Our evaluations on
commodity GPUs, an Nvidia TESLA, and an Intel PHI reveal the expected linear
scaling behavior when offloading larger workloads. For sub-second duties, the
efficiency of offloading was found to largely differ between devices. Moreover,
our findings indicate a negligible overhead over programming with the native
OpenCL API.Comment: 28 page
Destination-Language Proficiency in Cross-National Perspective: A Study of Immigrant Groups in Nine Western Countries
Immigrantsâ destination-language proficiency has been typically studied from a microperspective in a single country. In this article, the authors examine the role of macrofactors in a cross-national perspective. They argue that three groups of macrolevel factors are important: the country immigrants settle in (âdestinationâ effect), the sending nation (âoriginâ effect), and the combination between origin
and destination (âsettingâ or âcommunityâ effect). The authors propose a design that simultaneously observes multiple origin groups in multiple destinations. They present substantive hypotheses about language proficiency and use them to develop a series of macrolevel indicators. The authors collected and standardized 19 existing immigrant surveys for nine Western countries. Using multilevel techniques, their analyses show that origins, destinations, and settings play a significant role in immigrantsâ language proficiency.
Slisp: A Flexible Software Toolkit for Hybrid, Embedded and Distributed Applications
We describe Slisp (pronounced âEss-Lispâ), a hybrid LispâC programming toolkit for the development of scriptable and distributed applications. Computationally expensive operations implemented as separate C-coded modules are selectively compiled into a small Xlisp interpreter, then called as Lisp functions in a Lisp-coded program. The resulting hybrid program may run in several modes: as a stand-alone executable, embedded in a different C program, as a networked server accessed from another Slisp client, or as a
networked server accessed from a C-coded client. Five years of experience with Slisp, as well experience with other scripting languages such as Tcl and Perl, are summarized. These experiences suggest that Slisp will be most useful for mid-sized applications in which the kinds of scripting and embeddability features provided by Tcl and Perl can be extended in an efïŹcient manner to larger applications, while maintaining a
well-deïŹned standard (Common Lisp) for these extensions. In addition, the generality of Lisp makes Lisp a good candidate for an application-level communication language in distributed environments
Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction
We develop a natural language interface for human robot interaction that
implements reasoning about deep semantics in natural language. To realize the
required deep analysis, we employ methods from cognitive linguistics, namely
the modular and compositional framework of Embodied Construction Grammar (ECG)
[Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference
resolution problems and other issues related to deep semantics and
compositionality of natural language. This also includes verbal interaction
with humans to clarify commands and queries that are too ambiguous to be
executed safely. We implement our NLU framework as a ROS package and present
proof-of-concept scenarios with different robots, as well as a survey on the
state of the art
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