We propose a novel technique for adapting text-based statistical machine translation to deal with input from automatic speech recognition in spoken language translation tasks. We simulate likely misrecognition errors using only a source language pronunciation dictionary and language model (i.e., without an acoustic model), and use these to augment the phrase table of a standard MT system. The a...

The article presents a rule-based machine translation system from Northern Sami to Norwegian. grammatical analysis is done with Giellatekno and Divvun's North program for translation. We have written the transfer component (transfer lexicon rules) within framework of open Apertium. contains an evaluation translated text two different domains. texts score better on presentation content than flue...

We describe experiments on quality estimation to select the best translation among multiple options for a given source sentence. We consider a realistic and challenging setting where the translation systems used are unknown, and no relative quality assessments are available for the training of prediction models. Our findings indicate that prediction errors are higher in this blind setting. Howe...

Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is ...

This paper provides a novel model for English/Arabic Query Translation to search Arabic text, and then expands the Arabic query to handle Arabic OCR-Degraded Text. This includes detection and translation of word collocations, translating single words, transliterating names, and disambiguating translation and transliteration through different approaches. It also expands the query with the expect...

ATR has built a multi-language speech translation system called ATR-MATRIX. It consists of a spoken-language translation subsystem, which is the focus of this paper, together with a highly accurate speech recognition subsystem and a high-definition speech synthesis subsystem. This paper gives a road map of solutions to the problems inherent in spoken-language translation. Spokenlanguage transla...

We propose a method of automatic identification of various error types in machine translation output. The approach is mostly based on monolingual word alignment of the hypothesis and the reference translation. In addition to common lexical errors misplaced words are also detected. A comparison to manually classified MT errors is presented. Our error classification is inspired by that of Vilar (...

A method for multilingual review classification is described. In this classification task, machine translation techniques are used to remove language gaps in the dataset, but many translation errors occur as a side-effect. These errors cause a decrease in the review classification performance. To resolve this problem, we introduce a sentiment-oriented sentence filtering module to the process of...

In this paper, we investigate a novel approach to correcting grammatical and lexical errors in texts written by second language authors. Contrary to previous approaches which tend to use unilingual models of the user's second language (L2), this new approach uses a simple roundtrip Machine Translation method which leverages information about both the author’s first (L1) and second languages. We...

In this paper, a novel for Query Translation and Expansion for enabling English/Arabic CLIR for both normal and OCR-Degraded Arabic Text model has been proposed, implemented, and tested. First, an English/Arabic Word Collocations Dictionary has been established plus reproducing three English/Arabic Single Words Dictionaries. Second, a modern Arabic Corpus has been built. Third, a model for simu...