Add to ORKGIn this paper we present a statistical transliteration technique that is language independent. This technique uses statis-tical alignment models and Conditional Random Fields (CRF). Statistical align-ment models maximizes the probability of the observed (source, target) word pairs using the expectation maximization algo-rithm and then the character level align-ments are set to maximum posterior pre-dictions of the model. CRF has efficient training and decoding processes which is conditioned on both source and target lan-guages and produces globally optimal so-lution.
<p>We consider the task of generating transliterated word forms. To allow for a wide range of intera...
Automatic transliteration problem is to transcribe foreign words in one's own alphabet. Machine...
The system presented in this paper is based upon a phrase-based statistical machine transliteration ...
In this paper we present a statistical translit-eration technique that is language indepen-dent. Thi...
This paper proposes a novel noise-aware char-acter alignment method for bootstrapping sta-tistical m...
Motivated by phrase-based translation research, we present a transliteration system where char-acter...
This paper studies transliteration align-ment, its evaluation metrics and applica-tions. We propose ...
[[abstract]]This paper describes a framework for modeling the machine transliteration problem. The p...
We propose a language-independent method for the automatic extraction of transliteration pairs from ...
Although most of previous translitera-tion methods are based on a generative model, this paper prese...
We investigate three methods for integrat-ing an unsupervised transliteration model into an end-to-e...
Most foreign names are transliterated into Chinese, Japanese or Korean with approximate phonetic equ...
Transliteration of given parallel name en-tities can be formulated as a phrase-based statistical mac...
We present a high-precision, language-independent transliteration framework applicable to bilingual ...
Abstract: The work proposes a method of cross-lingual transliteration rules generation. Th...
<p>We consider the task of generating transliterated word forms. To allow for a wide range of intera...
Automatic transliteration problem is to transcribe foreign words in one's own alphabet. Machine...
The system presented in this paper is based upon a phrase-based statistical machine transliteration ...
In this paper we present a statistical translit-eration technique that is language indepen-dent. Thi...
This paper proposes a novel noise-aware char-acter alignment method for bootstrapping sta-tistical m...
Motivated by phrase-based translation research, we present a transliteration system where char-acter...
This paper studies transliteration align-ment, its evaluation metrics and applica-tions. We propose ...
[[abstract]]This paper describes a framework for modeling the machine transliteration problem. The p...
We propose a language-independent method for the automatic extraction of transliteration pairs from ...
Although most of previous translitera-tion methods are based on a generative model, this paper prese...
We investigate three methods for integrat-ing an unsupervised transliteration model into an end-to-e...
Most foreign names are transliterated into Chinese, Japanese or Korean with approximate phonetic equ...
Transliteration of given parallel name en-tities can be formulated as a phrase-based statistical mac...
We present a high-precision, language-independent transliteration framework applicable to bilingual ...
Abstract: The work proposes a method of cross-lingual transliteration rules generation. Th...
<p>We consider the task of generating transliterated word forms. To allow for a wide range of intera...
Automatic transliteration problem is to transcribe foreign words in one's own alphabet. Machine...
The system presented in this paper is based upon a phrase-based statistical machine transliteration ...