After decades of massive digitisation, an unprecedented number of historical documents are
available in digital format, along with their machine-readable texts. While this represents a …

After decades of massive digitisation, an unprecedented amount of historical documents is
available in digital format, along with their machine-readable texts. While this represents a …

Named entity recognition (NER) is the problem of locating and categorizing important nouns
and proper nouns in a text. In this chapter, we review the general state of research on entity …

Standard automatic metrics, eg BLEU, are not reliable for document-level MT evaluation.
They can neither distinguish document-level improvements in translation quality from …

Some languages lack large knowledge bases and good discriminative features for Name
Entity Recognition (NER) that can generalize to previously unseen named entities. One such …

We investigate three methods for integrating an unsupervised transliteration model into an
end-to-end SMT system. We induce a transliteration model from parallel data and use it to …

Transliteration is the process of converting words from a given source language alphabet to
a target language alphabet, in a way that best preserves the phonetic and orthographic …

In past, rule-based and statistical machine translation techniques were employed to solve
Urdu transliteration techniques. As mentioned in the literature, Urdu is considered as low …

In this paper, we propose different architectures for language independent machine
transliteration which is extremely important for natural language processing (NLP) …

The translation of proper nouns is not as easy as that of other parts of speech as this is more
challenging for certain reasons. The present article presents a descriptive study of proper …