This paper describes an example-based machine translation (EBMT) system which relays on various knowledge resources. Morphologic analyses abstract the surface forms of the languages to be translated. A shallow syntactic rule formalism is used to percolate features in derivation trees. Translation examples serve the decomposition of the text to be translated and determine the transfer of lexical...

In speech translation, recognition errors produced by the speech recognition process can cause parsing and translation errors. Because of this, the development of a robust error handling framework is quite essential to improve the performance of the speech translation system. Previously, a robust translation method was proposed by Wakita, which translates only reliable parts in utterances. In t...

The notion of “best of breed” among value-added machine translation technology providers is generally defined as providing access to the single best commercially available machine translation engine for each language pair. This paper describes the efforts of Amikai, Inc. to go beyond that definition of best of breed. Rather than relying on a single engine for each pair, we have written a progra...

In the spoken language translation pipeline, machine translation systems that are trained solely on written bitexts are often unable to recover from speech recognition errors due to the mismatch in training data. We propose a novel technique to simulate the errors generated by an ASR system, using the ASR system’s pronunciation dictionary and language model. Lexical entries in the pronunciation...

In spoken language translation (SLT), finding proper segmentation and reconstructing punctuation marks are not only significant but also challenging tasks. In this paper we present our recent work on speech translation quality analysis for German-English by improving sentence segmentation and punctuation. From oracle experiments, we show an upper bound of translation quality if we had human-gen...

With the active participation of users in product review platforms, online consumer-generated content, and, more specifically, user-generated reviews, have become a clear reference purchasing decision-making processes, which sometimes exceed impact advertising campaigns. A common feature most tourism platforms is use machine translation (MT) systems to immediately make reviews available various...

Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers explored visible-to-Mid-Wave (visible-to-MWIR) translation. In this paper, we investigated unsupervised visible-to-MWIR using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for full...

Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years. However, recent studies show that NMT generally produces fluent but inadequate translations (Tu et al. 2016; He et al. 2016). This is in contrast to conventional Statistical Machine Translation (SMT), which usually yields adequate but non-fluent translations. It is natural, th...

  In this article the possible effects of the translation technologies on the critical thinking and translation ability of the students of the Translation Studies would be studied through a pre-experimental method of research. The participants of this research were thirty one Iranian senior Translation Studies students at the age group of 20-26 who were selected based on their age, educational...