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}, { "first": "Soumik", "middle": [], "last": "Mandal", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Vinay", "middle": [], "last": "Kumar Mittal", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Vandan", "middle": [], "last": "Mujadia", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Iiit-Hyderabad", "middle": [ "Animesh" ], "last": "Mukherjee", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Iit", "middle": [], "last": "Kharagpur", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Aditi", "middle": [], "last": "Mukherjee", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Siddhartha", "middle": [], "last": "Mukherjee", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Samsung", "middle": [], "last": "R&d", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Partha", "middle": [], "last": "Pakray", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Michal", "middle": [], "last": "Ptaszynski", "suffix": "", "affiliation": {}, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "", "pdf_parse": { "paper_id": "2020", "_pdf_hash": "", "abstract": [], "body_text": [ { "text": "Research in Natural Language Processing (NLP) has taken a noticeable leap in recent years. The tremendous growth of information on the web and its easy access has stimulated a large interest in the field. India, with multiple languages and continuous growth of Indian language content on the web, makes a fertile ground for NLP research. Moreover, the industry is keenly interested in obtaining NLP technology for mass use. Internet search companies are increasingly aware of the large market for processing languages other than English. For example, search capability is needed for content in Indian and other languages. There is also a need for searching content in multiple languages, and making the retrieved documents available in the language of the user. As a result, a strong need is being felt for machine translation to handle this large instantaneous use. Information Extraction, Question Answering Systems, and Sentiment Analysis are also showing up as other business opportunities.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Preface", "sec_num": null }, { "text": "These needs have resulted in two welcome trends. First, there is a much wider student interest in getting into NLP at both postgraduate and undergraduate levels. Many students interested in computing technology are getting interested in natural language technology, and those interested in pursuing computing research are joining NLP research. Second, the research community in academic institutions and government funding agencies in India have joined hands to launch consortia projects to develop NLP products. Each consortium project is a multi-institutional endeavour working with a common software framework, common language standards, and common technology engines for all the different languages covered in the consortium. As a result, it has already led to the development of basic tools for multiple languages that are interoperable for machine translation, cross-lingual search, handwriting recognition, and OCR.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Preface", "sec_num": null }, { "text": "In this backdrop of increased student interest, greater funding, and most importantly, common standards and interoperable tools, there has been a spurt in research in NLP on Indian languages whose effects we have just begun to see. A great number of submissions reflecting good research is a heartening matter. There is an increasing realization to take advantage of features common to Indian languages in machine learning. It is a delight to see that such features are not just specific to Indian languages but to a large number of languages of the world, hitherto ignored. The insights so gained are furthering our linguistic understanding and will help in technology development for hopefully all languages of the world.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Preface", "sec_num": null }, { "text": "For machine learning and other purposes, linguistically annotated corpora using the common standards have become available for multiple Indian languages. They have been used for the development of basic technologies for several languages. A larger set of corpora are expected to be prepared in the near future.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Preface", "sec_num": null }, { "text": "These conference proceedings contain papers selected for presentation in technical sessions of ICON-2020. We are thankful to our excellent team of reviewers from all over the globe who deserve full credit for the hard work of reviewing the high-quality submissions with rich technical content. From 130 submissions, 66 papers were selected, 29 long papers, 34 short papers, 3 doctoral consortium papers, representing a variety of new and interesting developments, covering a wide spectrum of NLP areas and core linguistics. Besides presentations, the conference also hosted 2 tutorials, 1 workshop, 3 shared tasks, and 18 system demonstrations. ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Preface", "sec_num": null } ], "back_matter": [ { "text": "We are deeply grateful to Prof. David Yarowsky from John Hopkins University (USA), Prof. Iryna Gurevych from Technische Universit\u00e4t Darmstadt (Germany), and Prof. Eduard Hovy from Carnegie Mellon University for giving the keynote lectures at ICON. We also extend our heartfelt thanks to Dr Soujanya Poria, Singapore University of Technology and Design, Singapore for giving the invited talk at iii ICON.We thank all the area chairs for the various tracks at ICON 2020, especially, Sobha Lalitha Devi (Language Resources, NLP Language Documentation and Preservation), Ashwini Vaidya, Pawan Goyal (Syntax and Lexical Semantics), Praveen Kumar G S (Named Entity Recognition, Question Answering, Information Extraction, Dialogue Systems), Amitava Das, Radhika Mamidi (Sentiment and Emotion Analysis), Karunesh Arora, Sandipan Dandapat (Machine Translation), Vasudeva Varma, Dipankar Das (Summarization, Natural Language Generation, Information Retrieval and Text Mining), C V Jawahar (Multimodality, Speech Recognition, Speech Synthesis), Raksha Sharma, Nikesh Garera, (NLP for Digital Humanities, NLP for Education), Samar Husain (Ethics in NLP, Cognitive Modelling and Psycholinguistics), Karthik Sankaranarayanan, Ashutosh Modi (Machine Learning Applications to NLP, Interpretability and Explainability of NLP models). We also thank Gurpreet Singh Lehal, Sanjay Dwivedi, Rajeev R R, Sanjeev Gupta, Neeraj Mogla, Amba Kulkarni (Co-Chairs, Tools Contest), Sudip Kumar Naskar, Sriparna Saha (Co-Chairs, Workshop/Tutorial), Preethi Jyothi (Doctoral Consortium Chair) for taking the responsibilities of the events.We are thankful to the team members of the Artificial Intelligence-Natural Language Processing-Machine Learning (AI-NLP-ML) Group of the Department of Computer Science and Engineering for making the organization of the event at the Indian Institute of Technology Patna (IIT Patna) a success. We heartily express our gratitude to Pushpak Bhattacharyya, Asif Ekbal, Sriparna Saha, Soumitra Ghosh, Ratnesh Joshi, Prabhat Kumar Bharti, Gitanjali Singh, Tirthankar Ghosal, Apoorva Singh, and other AI-NLP-ML team members at IIT Patna for their timely help with sincere dedication to make this conference a success. We also thank and all those who came forward to help us with this task.Finally, we thank all the researchers who responded to our call for papers and all the participants of ICON-2020, without whose overwhelming response the conference would not have been a success. We wholeheartedly thank all the reviewers who accepted our invitation and spent their valuable time reviewing the papers to maintain their high international standards. 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Dependencies Salih Tuc and Burcu Can ThamizhiUDp: A Dependency Parser for Tamil Kengatharaiyer Sarveswaran and Gihan Dias Free Word Order in Sanskrit and Well-nestedness Sanal Vikram and Amba Kulkarni Technical Session XVI: Machine Translation-II Session Chair: Anoop Kunchukuttan English to Manipuri and Mizo Post-Editing Effort and its Impact on Low Resource Machine Translation Loitongbam Sanayai Meetei, Thoudam Doren Singh, Sivaji Bandyopadhyay, Mi- haela Vela and Josef van Genabith Improving Neural Machine Translation for Sanskrit-English Ravneet Punia, Aditya Sharma, Sarthak Pruthi and Minni Jain Leveraging Alignment and Phonology for low-resource Indic to English Neural Ma- chine Transliteration Parth Patel and Manthan Mehta +17:30-18:00 BUFFER +18:00-19:00 Keynote Lecture 3: David Yarowsky, John Hopkins University, USA Title: Translingual Learning of 1000+ Languages Session Chair: Prof. Dipti Misra Sharma +19:00-19:30 Valedictory Session xxiii Pre-conference: Friday, December 18, 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WEAVE Corpus: Annotating Synthetic Chemical Procedures in Patents with Chemical Named Entities Ravindra Nittala and Manish Shrivastava . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Increasing accuracy of a semantic word labelling tool based on a small lexicon Hugo Sanjurjo-Gonz\u00e1lez . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Treatment of optional forms in Mathematical modelling of P\u00e3n . ini Anupriya Aggarwal, Malhar Kulkarni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Automatic Hadith Segmentation using PPM Compression Taghreed Tarmom, Eric Atwell and Mohammad Alsalka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22", "html": null, "content": "", "type_str": "table" } } } }