The Cowichan problems are a suite for assessing the usability of parallel programming systems. By implementing these applications in Orca, many useful lessons were learned about the design and implementation of this parallel language.

We present a large Spanish-Catalan parallel corpus extracted from ten years of the paper edition of a bilingual Catalan newspaper. The produced corpus of 7.5 M parallel sentences (around 180 M words per language) is useful for many natural language applications. We report excellent results when building a statistical machine translation system trained on this parallel corpus. The Spanish-Catala...

The construction of parallel solutions for numerical problems relates diierent types of languages, for example, speciication languages, programming languages and reasoning languages. Each language has a diierent mechanism for expressing its semantics. An extension of a new speciication language, namely TLA + Lam91b], 1 is introduced, which will be used to specify and develop parallel solutions ...

Human Language Technologies use two main paradigms: rules and statistical models. Rule-based methods are more traditional, statistical tools relying on huge textual and spoken corpora are considered rather modern. Both are, however, sequential methods. The first elements of parallel processing are available today. The (near) future’s language technology should rely on parallel language processi...

This study investigates English as a Foreign Language (EFL) teachers’ needs and desires with regard to the in-service training courses (ITCs) programs in Marand, East Azerbaijan province, Iran. 21 EFL teachers at both junior (N=10) and senior high schools (N=11) participated in this study. The data concerning the participants’ mentioned needs and desires were gathered by means of a structured i...

Statistical machine translation (SMT) requires a parallel corpus between the source and target languages. Although a pivot-translation approach can be applied to a language pair that does not have a parallel corpus directly between them, it requires both source–pivot and pivot–target parallel corpora. We propose a novel approach to apply SMT to a resource-limited source language that has no par...

Statistical machine translation (SMT) requires a parallel corpus between the source and target languages. Although a pivot-translation approach can be applied to a language pair that does not have a parallel corpus directly between them, it requires both source–pivot and pivot–target parallel corpora. We propose a novel approach to apply SMT to a resource-limited source language that has no par...

In this paper, we describe a massively parallel programming language V and its application to describe of parallel image processing algorithms. V is designed so as to be independent from target machine architectures as much as possible, and to provide a framework for programmers to describe a wide variety of parallel algorithms easily. V is based on a functional language framework and enhanced ...

AbstructWe have compared the performance of four approaches for automatic language identification of speech utterances: Gaussian mixture model (GMM) classification; single-language phone recognition followed by languagedependent, interpolated n-gram language modeling (PRLM); parallel PRLM, which uses multiple single-language phone recognizers, each trained in a different language; and languaged...

We propose a Bayesian model of unsupervised semantic role induction in multiple languages, and use it to explore the usefulness of parallel corpora for this task. Our joint Bayesian model consists of individual models for each language plus additional latent variables that capture alignments between roles across languages. Because it is a generative Bayesian model, we can do evaluations in a va...