Transtech: development of a novel translator for Roman Urdu to English.
Clicks: 363
ID: 49846
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
363 views
71 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #97 of 235 articles by views in Heliyon
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 235 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Advances in machine and language translation immerge new fields and research opportunities for researchers, whereas Natural Language Processing and Computational Linguistics deal with communication between natural languages and their interaction. The objective of this research is to develop and test a novel tactic to solve the issue of translation from Roman Urdu to the English language. The approach used to construct this practical model is divided into three stages; each stage works out to achieve its desired task. Self-maintained corpus alongwith its corresponding tag-set is used for tokenization. The syntactical structure is covered by writing Urdu POS tagger based on grammatical rules. We prepared the grammatical structures of different sentences for Roman Urdu to English translation. Since Roman script can be expressed in numerous ways, our grammatical structures fulfill the maximum possible needs of writing and produce the best possible English translation. We entered a sentence in Roman Urdu which gave the best possible translation in the English language. In comparison with Google Translator, Transtech worked better and gives more accurate results.
| Reference Key |
masroor2019transtechheliyon
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Masroor, Hafsa;Saeed, Muhammad;Feroz, Maryam;Ahsan, Kamran;Islam, Khawar; |
| Journal | Heliyon |
| Year | 2019 |
| DOI |
10.1016/j.heliyon.2019.e01780
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.