
Dr. Priyanka Jain
Associate Director, C-DAC Delhi, India
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Priyanka Jain is an Associate Director in Artificial Intelligence and Human Centric Computing Group (AI & HCC), C-DAC, Delhi. C-DAC (Centre for Development of Advanced Computing), a premier R&D organization and scientific society of the Ministry of Electronics and Information Technology (MeitY), Government of India. With over 19 years’ experience in Applied Artificial Intelligence Group (AAI-G), C-DAC, Pune, Dr. Priyanka has been the key contributor in the core research activities of Artificial Intelligence, Natural language processing, Machine Translation related mission mode projects of national importance. Apart from his regular responsibilities of research project execution at C-DAC, she is an active member of IEEE Standard Association NLP Pre-Standard Working Group (2020).
Dr. Priyanka is the recipient of “Augmenting Writing Skills for Articulating Research (AWSAR-2019)” by Department of Science and Technology (DST) for best 100 entries of ongoing Ph. D. work. The award ceremony was graced by Hon’ble President of India Sh. R. N. Kovind at Vigyan Bhavan, New Delhi at National Science Day dated 28 Feb, 2020. She has received Award for appreciation for meritorious service, contribution, role, efforts and initiative to the activities of C-DAC in 2010. Received the Certificate in 2010 for the Key-Contribution to the development of Mantra-Rajbhasha Project using state-of-the-art and cutting-edge technologies and solutions for Language Computing implemented by the AAI-G, C-DAC, Pune from Department of Official Language (DoL), MHA, India. She also has received a Certificate for Outstanding Contribution in the development of Mantra-Rajya Sabha, a Unique Machine Translation System launched on 29th August 2007 by Vice President of India & Chairman Rajya Sabha.
She has 14 Copyright(s) awarded in her credit. She has 32 impactful publications to her credit, majorly in (2 chapters in books, 8 research papers in peer reviewed international Journals, 20 conference papers and two poster presentations). She is a reviewing member of impactful journals namely; ACM's TALLIP Journal, Elsevier’s Procedia Computer Science journal, Journal of Artificial Intelligence, IT Professional, and many international Conferences. She has shared her knowledge in many stimulating events including ‘Women in Data Science’ (WIDS) Pune & Noida, Wei-HACK-2.0 (BVPIEEE) and more. She has supervised many graduate and post-graduate students as an intern where majority of the research topics focused on the core research and applications in Human centric computing.
In the capacity of techno-functional manager, her role in organization is to in project planning, architecture & design, monitoring, communication and supporting documentation for many real-time projects. In the role of Project leader, she served the organization for major projects like Speech-to-Speech (S2S) MT (2012 -2016), ILMT: Indian to Indian Languages MT (2006 -2011), MANTRA-Rajbhasha (2004 -2010), PRAVACHAK-Rajbhasha (2002 -2005), MANTRA-Rajya Sabha (2001 – 2007) and Learn Indian Languages through Artificial Intelligence (LILA: Rajbhasha) (2000 – 2001). She was key-technical coordinator for MeitY sponsored consortia-based major research projects like English to Indian languages Machine Translation System; EILMT Phase-I (2006 - 2010) and Phase-II (2010 - 2016) where C-DAC, Pune played the role of consortia leader. She contributed for the “Hindi to English Machine Translation System for Judicial Domain” (2017 - 2020) for Hon’ble Supreme Court. She was part of planning and initiation phase of MT platform ‘Bahubhashak (2019 - 2020)’ under the national level mission of MeitY.
Dr. Priyanka has completed her Doctoral degree in (Computer Science), titled “Preksha: A Hindi Text Visualizer”, from KBCNMU, Jalgaon, MS. Having research-oriented personage, she derives new approaches and algorithms to extend the coverage of knowledge. Apart from AI and NLP, her area of interest is Cognitive Computing, Brain Computer Interface, High Performance Computing, Security and Computer Vision.
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Automatic Text Visualization (ATV) or Text to Scene (TTS) conversation is relatively a new research area covering the domain of Artificial Intelligence, Natural Language Processing, Cognitive computing, Knowledge engineering, Computer Graphics and Psycho-linguistic. ATV is the process of language understanding of an input language text and its utilization as a 3D scene/ virtual environment. ATV has usage in real time applications like language learning for the persons with specific learning disabilities, knowledge transformation (globalization), text summarization, encrypting information for security and Games & entertainment. There are few works reported in English and other European languages but none for Indian Language.
We are going to talk about an end-to-end case study for Language Hindi, which is a Morphological rich free word order (MoR-FWO) language with many challenges in its computational processing. The modular architecture is worked upon with pluggable components that is extendible to scope. It consists of three major processing steps: language processing, knowledge base creation and scene generation. We have designed subjective evaluation for the work in absence of standards automatic methodologies on evaluations of ATV systems. Our strategic plan of evaluation carried out to cover Intelligibility, Fidelity and Complexity features of the system. For moderate complex inputs for human to visualize i.e. 1.77/5 the scores are achieved as 3.01/5 i.e. ‘Very Accurate’ and 2.84 /5 ‘Fairly Intelligent’.
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