Conventional speech translation systems wait until the end of the input sentence before starting translation, causing a large delay in the translation process. Methods have been proposed to reduce this delay by dividing the input utterance on pause boundaries, but while these methods have proven useful on speech translation of language pairs with similar word order, they are insensitive to ling...

The statistical machine translation approach is highly popular in automatic translation research area and promising approach to yield good accuracy. Efforts have been made to develop Urdu to Punjabi statistical machine translation system. The system is based on an incremental training approach to train the statistical model. In place of the parallel sentences corpus has manually mapped phrases ...

This paper describes various noise robustness issues in a speech-to-speech translation system. We present quantitative measures for noise robustness in the context of speech recognition accuracy and speech-to-speech translation performance. To enhance noise immunity, we explore two approaches to improve the overall speech-to-speech translation performance. First, a multi-style training techniqu...

This paper describes various noise robustness issues in a speech-to-speech translation system. We present quantitative measures for noise robustness in the context of speech recognition accuracy and speech-to-speech translation performance. To enhance noise immunity, we explore two approaches to improve the overall speech-to-speech translation performance. First, a multi-style training techniqu...

Statistical Machine Translation (SMT) usually utilizes contextual information to disambiguate translation candidates. However, it is often limited to contexts within sentence boundaries, hence broader topical information cannot be leveraged. In this paper, we propose a novel approach to learning topic representation for parallel data using a neural network architecture, where abundant topical c...

Translation ambiguity is a major problem in dictionary-based cross-language information retrieval. To attack the problem, indirect disambiguation approaches, which do not explicitly resolve translation ambiguity, rely on query-structuring techniques such as a structured Boolean model and Pirkola’s method. Direct disambiguation approaches try to assign translation probabilities to translation eq...

Accurate high-coverage translation is a vital component of reliable cross language information access (CLIA) systems. While machine translation (MT) has been shown to be effective for CLIA tasks in previous evaluation workshops, it is not well suited to specialized tasks where domain specific translations are required. We demonstrate that effective query translation for CLIA can be achieved in ...

In this paper, a variant of a spectral clustering algorithm is proposed for bilingual word clustering. The proposed algorithm generates the two sets of clusters for both languages efficiently with high semantic correlation within monolingual clusters, and high translation quality across the clusters between two languages. Each cluster level translation is considered as a bilingual concept, whic...