The translation quality of machine systems depends on the parallel corpus used for training, in particular quantity and corpus. However, building a high-quality large-scale is complex expensive, particularly specific domain Therefore, data augmentation techniques are widely translation. input back-translation method monolingual text, which available from many sources, therefore this can be easi...

There are many approaches to increase web service based machine translation result. However, perfect result alone does not guarantee the quality of translation service or user satisfaction. This paper proposes framework to improve translation service by using non functional attributes information. In this paper, we present methodology to measure quality of composite translation service using ex...

We have conducted initial experiments with statistical machine translation between English and Swedish based on the Moses toolkit and the Europarl corpus. The main aim was to decrease processing times without harming translation quality by changing the settings in Moses and for the parameter tuning. The experiments show that translation and tuning times can be cut around 10 times without harmin...

The varying quality of machine translation (MT) poses a problem for language service providers (LSPs) which want to use MT to make the translation production process more efficient. In this user study we describe the MT confidence score we developed. It predicts the quality of a segment translated by MT and it is fully integrated into the translation workflow.

Previous comparisons of document and query translation suffered difficulty due to differing quality of machine translation in these two opposite directions. We avoid this difficulty by training identical statistical translation models for both translation directions using the same training data. We investigate information retrieval between English and French, incorporating both translations dir...

There are many approaches to increase web service based machine translation result. However, perfect result alone does not guarantee the quality of translation service or user satisfaction. This paper proposes framework to improve translation service by using non functional attributes information. In this paper, we present methodology to measure quality of composite translation service using ex...

This paper proposes machine learning techniques, which help disambiguate word meaning. These methods focus on considering the relationship between a word and its surroundings, described as context information in the paper. Context information is produced from rule-based translation such as part-ofspeech tags, semantic concept, case relations and so on. To automatically extract the context infor...

Statistical Machine Translation (SMT) is a well-known and well established datadriven approach used for language translation. The focus of this work is to develop a statistical machine translation system for Sri Lankan languages, Sinhala and Tamil language pair. This paper presents a systematic investigation of how SinhalaTamil SMT performance varies with the amount of parallel training data us...