Language modeling is an important part for both speech recognition and machine translation systems. Adaptation has been successfully applied to language models for speech recognition. In this paper we present experiments concerning language model adaptation for statistical machine translation. We develop a method to adapt language models using information retrieval methods. The adapted language models drastically reduce perplexity over a general language model and we can show that it is possible to improve the translation quality of a statistical machine translation using those adapted language models instead of a general language model. 1
(Now with TEMIC SDS GmbH, Ulm, Germany). It has been demonstrated repeatedly that the acoustic model...
Abstract. In this paper, we investigate the language model (LM) adaptation issue for Statis-tical Ma...
Most work in syntax-based machine trans-lation has been in translation modeling, but there are many ...
Abstract. In this paper we present experiments concerning translation model adaptation for statistic...
We explore unsupervised language model adaptation techniques for Statistical Machine Translation. Th...
Language modeling is critical and indispensable for many natural language ap-plications such as auto...
Copyright © 2015 ISCA. Direct integration of translation model (TM) probabilities into a language mo...
In this thesis we develop and evaluate a general framework for domain-adaptation of statistical mach...
A novel variation of modified KNESER-NEY model using monomial discounting is presented and integrate...
[[abstract]]Statistical language modeling, which aims to capture the regularities in human natural l...
Spoken language translation (SLT) exists within one of the most challenging intersections of speech ...
The problem of language model adaptation in statistical machine translation is considered. A mixtur...
This paper describes a novel target-side syntactic language model for phrase-based statistical machi...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
Statistical machine translation (SMT) systems use statistical learning methods to learn how to trans...
(Now with TEMIC SDS GmbH, Ulm, Germany). It has been demonstrated repeatedly that the acoustic model...
Abstract. In this paper, we investigate the language model (LM) adaptation issue for Statis-tical Ma...
Most work in syntax-based machine trans-lation has been in translation modeling, but there are many ...
Abstract. In this paper we present experiments concerning translation model adaptation for statistic...
We explore unsupervised language model adaptation techniques for Statistical Machine Translation. Th...
Language modeling is critical and indispensable for many natural language ap-plications such as auto...
Copyright © 2015 ISCA. Direct integration of translation model (TM) probabilities into a language mo...
In this thesis we develop and evaluate a general framework for domain-adaptation of statistical mach...
A novel variation of modified KNESER-NEY model using monomial discounting is presented and integrate...
[[abstract]]Statistical language modeling, which aims to capture the regularities in human natural l...
Spoken language translation (SLT) exists within one of the most challenging intersections of speech ...
The problem of language model adaptation in statistical machine translation is considered. A mixtur...
This paper describes a novel target-side syntactic language model for phrase-based statistical machi...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
Statistical machine translation (SMT) systems use statistical learning methods to learn how to trans...
(Now with TEMIC SDS GmbH, Ulm, Germany). It has been demonstrated repeatedly that the acoustic model...
Abstract. In this paper, we investigate the language model (LM) adaptation issue for Statis-tical Ma...
Most work in syntax-based machine trans-lation has been in translation modeling, but there are many ...