This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the translation task of the ACL 2013 Eighth Workshop on Statistical Machine Translation (WMT 2013). We participated in the evaluation campaign for the French-English and German-English language pairs in both translation directions. Both hierarchical and phrase-based SMT systems are app...

47 Abstract—This paper relates a methodology to include some semantic information early in the statistical language model for Automatic Speech Recognition (ASR). This work is done in the framework of a global speech-to-speech translation project. An Interchange Format (IF) based approach, representing the meaning of phrases independently of languages, is adopted. The methodology consists in int...

Graphical models have been widely used to describe complex statistical models and to communicate these models to people who do not have a statistical background. In this paper we discus the WinBUGS software package which is based on these two ideas. A declarative language, the BUGS language, has been developed to describe complex statistical models. This language is processed by a compiler to p...

We describe a method for developing a statistical language model (SLM) with high keyword spotting accuracy for a natural language interface (NLI). The NLI is based on the Adaptive Agent Oriented Software Architecture (AAOSA). Our experience shows that this method provides for rapid development of an SLM that is well suited to the requirements of the agent-oriented NLI. Experiment results show a...

Since the quality of the language model directly affects the performance of the spoken dialog system (SDS), we should use a statistical language model (LM) trained with a large amount of data that is matched to the task domain. When porting an SDS to another language, however, it is costly to re-collect a large amount of user utterances in the target language. We thus use the language resources...

In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models in statistical machine translation: a backward language model that augments the conventional forward language model, and a mutual information trigger model which captures long-distance dependencies that go beyond the s...

Parallel corpora play a vital role in Statistical Machine Translation. Nonavailability of these corpora is a major barrier for adding new languages pairs. In this paper, we propose a new hybrid approach for English-French machine translation combining a cross-language search engine and a statistical language model trained from a monolingual corpus. The cross-language search engine returns the t...

this study had two main steps. the first one was introducing and examining the long’s model of needs analysis (na) for distinguishing the general language needs. by doing the first step, we tried to recognize the shortages of long’s model, in the second step to realize the general language needs of persian language learners and find out what language functions are needed to be learned for gener...

This paper presents two studies, first a statistical analysis for three languages i.e. Hindi, Punjabi and Nepali and the other, development of language models for three Indian languages i.e. Indian English, Punjabi and Nepali. The main objective of this study is to find distinction among these languages and development of language models for their identification. Detailed statistical analysis h...