ICBSLP 2019 is honored to have Professor Girish Nath Jha as a keynote speaker. He will speak on "LT Resource Crunch - challenges and opportunities for South Asian languages"
Prof. Girish Nath Jha teaches Computational Linguistics at the School of Sanskrit & Indic Studies in Jawaharlal Nehru University (JNU) and is currently the Dean of the school. He also holds concurrent appointments in JNU’s Center of Linguistics, Special Center of E-Learning and is an Associated Faculty in the ABV School of Management and Entrepreneurship. Prof Jha was previously the director of JNU’s International Collaboration during 2016-18.
His research interests include Indian languages corpora and standards, Sanskrit and Hindi linguistics, Science & Technology in ancient texts, Lexicography, Machine Translation, e-learning, web based technologies, RDBMS, software design and localization. Details on his work can be obtained from http://sanskrit.jnu.ac.in . Prof Jha has done collaborative research with the Center for Indic Studies, University of Massachusetts, Dartmouth, MA, USA as "Mukesh and Priti Chatter Distinguished Professor of History of Science" during 2009-12, has been a visiting professor at the Yogyakarta State University, Indonesia in 2013. He was awarded DAAD fellowships twice in 2014 and 2016 to teach Computational Linguistics in the Digital Humanities department at University of Würzburg, Germany and has been a visiting Professor at the University of Florence in the summer of 2016.
Prof. Jha did his M.A., M.Phil. and Ph.D. in Linguistics (Computational Linguistics) from JNU and then got another masters degree in Linguistics (specializing in Natural Language Interface) from University of Illinois, Urbana Champaign, USA in 1999. Since then he worked as software engineer and software development specialist in USA before joining JNU in 2002. Prof Jha has books published from publishers like Springer Verlag, Cambridge Scholar Publishing and has over 133 research papers/presentations/publications and over 178 invited talks. Prof Jha has had several consultancies including those from Nuance, Swiftkey, Microsoft Research USA, Microsoft Research India, Microsoft Corporation, Linguistic Data Consortium (University of Pennsylvania), University of Massachusetts Dartmouth, EZDI among others. Prof Jha has completed several sponsored projects for Indian language technology development and has led a consortium of 17 Indian universities/institutes for developing corpora and standards for Indian languages sponsored by Ministry of Electronics and IT (MEITY), Govt. of India.
Prof Jha has been chair/co-chair for at least 13 international seminars/conferences and has been nominated member of more than 30 committees. He was nominated to the editorial board of a leading journal from Springer and has been a reviewer of many leading journals and proceedings in the area of NLP. He has supervised 42 M.Phil. and 50 Ph.D. students. Prof Jha's efforts in collaboration with software industry has led to the development of key technologies for Indian languages including English-Urdu MT for Microsoft Bing Translator, predictive keyboards for several Indian languages by Swiftkey. His awards include Datta Peetha award for Sanskrit linguistics (2017), KECSS Felicitation award for promotion of Sharada script (2016)
Dr. Niladri Sekhar Dash works as Associate Professor in Linguistic Research Unit, Indian Statistical Institute, Kolkata. For the last 25 years, he is working in the area of Corpus Linguistics, Language Technology, Language Documentation and Digitization, Computational Lexicography, Computer Assisted Language Teaching, and Manual and Machine Translation.
Dr. Dash received Visiting Fellowship of the British Academy, UK (2018). To his credit, he has published 17 research monographs and 260 research papers in peer-reviewed international and national journals, anthologies, and conference proceedings.
Dr. Dash acts as Guest Faculty of School of Languages and Linguistics, Jadavpur University, Kolkata; Guest Faculty of Dept. of Linguistics, University of Calcutta, Kolkata; and Visiting Research Fellow of the School of Psychology and Clinical Language Science, University of Reading, UK (2018-2021).
As an invited speaker, Dr. Dash has delivered lectures at more than 40 Universities and institutes in India and abroad. He acts as a Consultant for several multinational organizations working on Language Technology and Natural Language Processing. Dr. Dash has acted as Principal Investigator for 15 projects funded by DeitY, MeitY, & MoSPI, Govt. of India. He is the Editor-in-Chief of Journal of Advanced Linguistic Studies – a peer-reviewed international journal of linguistics and Editorial Board Member for 5 international journals. He is Member of several Linguistic Associations across the world and a regular Ph.D. Thesis Examiner of several Indian and foreign Universities.
At present Dr. Dash is working on Digital Pronunciation Dictionary, Contextualized Word Sense Cognition, Digital Lexical Profile, Parallel Translation Corpus, Bilingual Lexical Database, POS Tagging, Computer Assisted Language Teaching, Endangered Language Documentation and Digitization, and Human and Machine Translation, etc.
Details of Dr. Dash are at: https://sites.google.com/site/nsdashisi/home/
Niladri Sekhar Dash
Linguistic Research Unit
Indian Statistical Institute, Kolkata
Every natural language has a large set of words which are semantically quite productive. When these words are used in a piece of text, they vary in meaning. It is noted that the context, where these words are used, plays an explicit (rarely implicit) and active (rarely passive) role to influence these forms to generate new context-based functions and meanings. The newly acquired meanings may vary from the original meaning which they usually derive from the source of their origin (i.e., etymology). This phenomenon of words in a natural language creates tremendous problems relating to understanding and describing meanings of words in general; cognition of semantic-cum-lexical functions of words in texts; representation of word meanings in machine learning algorithms; deciphering actual sense of polysemous words in information retrieval and machine translation; training the language learners in the act of learning word meanings; and in presenting the word meanings in dictionaries. In essence, a word of a natural language is a bundle of linguistic information relating to phonology, etymology, morphology, morphophonemics, syntax, lexicology, semantics, morphosyntax, grammar, text, metaphor, discourse, pragmatics, world knowledge and others (Pinker 1995: 344). Therefore, it is not easy to capture all types of information just by looking at its surface form or at its orthography. We require a versatile system along with our native language intuition to decipher all possible explicit and implicit senses of words used in a piece of text. A systematic study of meaning variation of words may help us to establish the notion of semantic indeterminacy and sense gradience (Leech, Francis, & Xu 1994) in the broader domain of language cognition. All these issues are addressed in this present talk with a focus on the Bangla language. It also proposes a cognitive-cum- computational method for understanding the actual contextualized meaning of words with reference to their usage in texts. This method (AIMS) is experimented and validated with a large amount of data retrieved from a Bangla written text corpus.