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 translation approach. We demonstrate that the extracted dictionary is accurate and of high recall (F1-score 0.8). Our lexicon contains not only single words but also multi-word expressions, and is freely available. Our experiments focus on Katakana-English lexicon construction, however it would be possible to apply the proposed methods to transliteration...
We propose a language-independent method for the automatic extraction of transliteration pairs from ...
Machine transliteration is a method for automatically converting words in one language into phonetic...
been published. We describe these previous research results in section 2. In this paper, we propose ...
Transliteration is the rendering in one language of terms from another language (and, possibly, anot...
We present a high-precision, language-independent transliteration framework applicable to bilingual ...
This paper proposes a novel approach to automating the construction of transliterated-term lexicons....
[[abstract]]This paper describes a framework for modeling the machine transliteration problem. The p...
It has been shown so far that using transliteration rules to extract Japanese Katakana and English w...
This paper presents a framework for extracting English and Chinese transliterated word pairs from pa...
This paper proposes a method of finding correspondences of arbitrary length word sequences in aligne...
This paper proposes a method of automatic transliteration from English to Japanese words. Our method...
This article describes the implementation of algorithms for generating a dictionary of Japanese scie...
Technical-term translation represents one of the most difficult tasks for human translators since (1...
New words such as names, technical terms, etc appear frequently. As such, the bilingual lexicon of a...
Most foreign names are transliterated into Chinese, Japanese or Korean with approximate phonetic equ...
We propose a language-independent method for the automatic extraction of transliteration pairs from ...
Machine transliteration is a method for automatically converting words in one language into phonetic...
been published. We describe these previous research results in section 2. In this paper, we propose ...
Transliteration is the rendering in one language of terms from another language (and, possibly, anot...
We present a high-precision, language-independent transliteration framework applicable to bilingual ...
This paper proposes a novel approach to automating the construction of transliterated-term lexicons....
[[abstract]]This paper describes a framework for modeling the machine transliteration problem. The p...
It has been shown so far that using transliteration rules to extract Japanese Katakana and English w...
This paper presents a framework for extracting English and Chinese transliterated word pairs from pa...
This paper proposes a method of finding correspondences of arbitrary length word sequences in aligne...
This paper proposes a method of automatic transliteration from English to Japanese words. Our method...
This article describes the implementation of algorithms for generating a dictionary of Japanese scie...
Technical-term translation represents one of the most difficult tasks for human translators since (1...
New words such as names, technical terms, etc appear frequently. As such, the bilingual lexicon of a...
Most foreign names are transliterated into Chinese, Japanese or Korean with approximate phonetic equ...
We propose a language-independent method for the automatic extraction of transliteration pairs from ...
Machine transliteration is a method for automatically converting words in one language into phonetic...
been published. We describe these previous research results in section 2. In this paper, we propose ...