Modern automated lexicon generation methods usually require parallel corpora, which are not available for most language pairs .

However, for most language pairs parallel bilingual corpora either do not exist or are at best small and unrepresentative of the general language.

Pivot language approaches deal with the scarcity of bilingual data for most language pairs by relying on the availability of bilingual data for each of the languages in question with a third, pivot, language.

We chose a language pair for which basically no parallel corpora existz, and that do not share ancestry or writing system in a way that can provide cues for alignment.

These considerations lead us to believe that our choice of language pair is more challenging than, for example, a pair of European languages.

For other language pairs lemmatization may be needed.

The limited availability of parallel corpora of sufficient size for most language pairs restricts the usefulness of these methods.

(2009) used many input bilingual lexicons to create bilingual lexicons for new language pairs .

Three human annotators who are fluent in the two languages manually annotated N-to-N sentence alignments for each language pairs (KR-EN, KR-CH, KR-JP).

By keeping only the sentence chunks whose Korean chunk appears in all language pairs , we were left with 859 sentence chunk pairs.

The subjectivity analysis systems are evaluated with all language pairs with kappa and Pearson’s correlation coefficients.

This indicates that transliteration is useful for more than only translating OOV words for language pairs like Hindi-Urdu.

In closely related language pairs such as Hindi-Urdu with a significant amount of vocabulary overlap,

The difference of 2.35 BLEU points between M1 and Pbl indicates that transliteration is useful for more than only translating OOV words for language pairs like Hindi-Urdu.

We present a novel scheme to apply factored phrase-based SMT to a language pair with very disparate morphological structures.

12The experience with MERT for this language pair has not been very positive.

In order to alleviate the lack of large scale parallel corpora for the English—Turkish language pair , we experimented with augmenting the training data with reliable phrase pairs obtained from a previous alignment.