Rashid Ahmad


2019

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Kunji : A Resource Management System for Higher Productivity in Computer Aided Translation Tools
Priyank Gupta | Manish Shrivastava | Dipti Misra Sharma | Rashid Ahmad
Proceedings of the 16th International Conference on Natural Language Processing

Complex NLP applications, such as machine translation systems, utilize various kinds of resources namely lexical, multiword, domain dictionaries, maps and rules etc. Similarly, translators working on Computer Aided Translation workbenches, also require help from various kinds of resources - glossaries, terminologies, concordances and translation memory in the workbenches in order to increase their productivity. Additionally, translators have to look away from the workbenches for linguistic resources like Named Entities, Multiwords, lexical and lexeme dictionaries in order to get help, as the available resources like concordances, terminologies and glossaries are often not enough. In this paper we present Kunji, a resource management system for translation workbenches and MT modules. This system can be easily integrated in translation workbenches and can also be used as a management tool for resources for MT systems. The described resource management system has been integrated in a translation workbench Transzaar. We also study the impact of providing this resource management system along with linguistic resources on the productivity of translators for English-Hindi language pair. When the linguistic resources like lexeme, NER and MWE dictionaries were made available to translators in addition to their regular translation memories, concordances and terminologies, their productivity increased by 15.61%.

2013

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Dashboard: A Tool for Integration, Validation, and Visualization of Distributed NLP Systems on Heterogeneous Platforms
Pawan Kumar | Rashid Ahmad | Banshi Chaudhary | Mukul Sinha
The Companion Volume of the Proceedings of IJCNLP 2013: System Demonstrations