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Identification of Boosters as Metadiscourse across Punjabi and Urdu Languages: A Machine Translation Approach

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Boosters are said to function appropriately as metadiscourse features across languages. This study, therefore, aimed to investigate the functions and appropriateness of the metadiscourse features across Punjabi and Urdu languages. For this purpose, a list of 79 boosters (as metadiscourse features) was considered that (boosters) were first transliterated across Punjabi and Urdu languages employing a machine translation process. Punjabi translation was carried through ‘Akhar’ (a software), and Punjabi corpus (a tool). Whereas Urdu translation was realized through online Urdu thesaurus, and ‘ijunoon’ (an online dictionary). Machine transliteration was followed by manual cleansing of Punjabi and Urdu translated wordlists that helped identify boosters in the corpora. Appropriateness of the identified boosters was then realized through expert opinion and Punjabi corpus (for the Punjabi language), and expert opinion, online Urdu thesaurus, and Urdu WordNet (for the Urdu language). This process further guided about how to; make wordlists, filter as well as verify translated words, and offer interactional and interactive metadiscourse categories across Punjabi and Urdu languages.
Title: Identification of Boosters as Metadiscourse across Punjabi and Urdu Languages: A Machine Translation Approach
Description:
Boosters are said to function appropriately as metadiscourse features across languages.
This study, therefore, aimed to investigate the functions and appropriateness of the metadiscourse features across Punjabi and Urdu languages.
For this purpose, a list of 79 boosters (as metadiscourse features) was considered that (boosters) were first transliterated across Punjabi and Urdu languages employing a machine translation process.
Punjabi translation was carried through ‘Akhar’ (a software), and Punjabi corpus (a tool).
Whereas Urdu translation was realized through online Urdu thesaurus, and ‘ijunoon’ (an online dictionary).
Machine transliteration was followed by manual cleansing of Punjabi and Urdu translated wordlists that helped identify boosters in the corpora.
Appropriateness of the identified boosters was then realized through expert opinion and Punjabi corpus (for the Punjabi language), and expert opinion, online Urdu thesaurus, and Urdu WordNet (for the Urdu language).
This process further guided about how to; make wordlists, filter as well as verify translated words, and offer interactional and interactive metadiscourse categories across Punjabi and Urdu languages.

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