Transliteration is a process of transcribing a word of the source language into the target language such that when the native speaker of the target language pronounces it, it sounds as the native pronunciation of the source word. Statistical techniques have brought significant advances and have made real progress in various fields of Natural Language Processing (NLP). In this paper, we have ana...

We present a transliteration algorithm based on sound and spelling mappings using nite state machines. The transliteration models can be trained on relatively small lists of names. We introduce a new spelling-based model that much more accurate than state-of-the-art phonetic-based models and can be trained on easier-to-obtain training data. We apply our transliteration algorithm to the translit...

Article history: Received date: 11 September, 2016 Review date: 12 October 2016 Accepted date:13 November 2016 Printed on line: 5 January 2017 Abstract Purpose: The purpose of the current study was to investigate the effect of cognitive-behavioral therapy on Young's areas of manipulative schema in spouses of veterans with Post traumatic stress disorder (PTSD). Materials & Methods: A...

[7-bit encoding, transliteration] We propose a general strategy for deriving 7-bit encodings for texts in languages which use an alphabetic non-Roman script, like Arabic, Persian, Sanskrit and many other Indic scripts, and for which there is some transliteration convention using Roman letters with additional diacritical marks. These schemes, which we will call \meta-transliterations", are based...

This report presents the results from the Machine Transliteration Shared Task conducted as part of The Sixth Named Entities Workshop (NEWS 2016) held at ACL 2016in Berlin, Germany. Similar to previous editions of NEWS Workshop, the Shared Task featured machine transliteration of proper names over 14 different language pairs, including 12 different languages and two different Japanese scripts.A ...

In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain. Translation pairs are extracted by filtering a large list of transliteration candidates generated automatically from a phrase table trained on parallel corpora. Filtering uses a novel transliteration similarity measure based on a discriminative phrase-based machine tra...

This paper describes our syllable-based phrase transliteration system for the NEWS 2012 shared task on English-Chinese track and its back. Grapheme-based Transliteration maps the character(s) in the source side to the target character(s) directly. However, character-based segmentation on English side will cause ambiguity in alignment step. In this paper we utilize Phrase-based model to solve ma...

Most current machine transliteration systems employ a corpus of known sourcetarget word pairs to train their system, and typically evaluate their systems on a similar corpus. In this paper we explore the performance of transliteration systems on corpora that are varied in a controlled way. In particular, we control the number, and prior language knowledge of human transliterators used to constr...